Healthcare (1962-present)
2025 (10)
Computing (general) / ACM Computing Surveys
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Computing (general) / IEEE Computer
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Enterprise Computing / IEEE IT Professional
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2024 (96)
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Computing (specialised) / IEEE Pervasive Computing
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Computing (general) / PhD Theses
UX & Human Factors / IEEE Computer Graphics & Applications
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2023 (131)
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UX & Human Factors / IEEE Multimedia
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2022 (122)
Computing (general) / Communications of the ACM
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Computing (general) / IEEE Computer
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Computing (specialised) / IEEE Pervasive Computing
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Software Engineering / ACM queue (FREE)
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Software Engineering / IEEE Software
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Enterprise Computing / IEEE IT Professional
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UX & Human Factors / IEEE Multimedia
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Computing (general) / PhD Theses
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Computing (specialised) / IEEE Security & Privacy
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2021 (144)
Computing (general) / Communications of the ACM
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Computing (general) / IEEE Computer
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Computing (general) / ACM Computing Surveys
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UX & Human Factors / IEEE Computer Graphics & Applications
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Software Engineering / IEEE Software
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Enterprise Computing / IEEE IT Professional
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Computing (specialised) / IEEE Internet Computing
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Computing (specialised) / IEEE Intelligent Systems
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Computing (specialised) / IEEE Pervasive Computing
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Computing (general) / PhD Theses
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Computing (specialised) / IEEE Computing in Science & Engineering
| 2021 |
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Software Engineering / GOTO Conference Videos (FREE)
| 2021 |
|
2020 (104)
Computing (general) / Communications of the ACM
| 2020 |
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Computing (general) / IEEE Computer
| 2020 |
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UX & Human Factors / ACM interactions
| 2020 |
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UX & Human Factors / IEEE Multimedia
| 2020 |
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| 2020 |
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Computing (specialised) / IEEE Intelligent Systems
| 2020 |
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Computing (specialised) / IEEE Pervasive Computing
| 2020 |
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Computing (specialised) / IEEE Internet Computing
| 2020 |
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Computing (general) / PhD Theses
| 2020 |
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2019 (113)
Computing (general) / Communications of the ACM
| 2019 |
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Hardware and Microprocessor Systems / IEEE Micro
| 2019 |
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UX & Human Factors / IEEE Multimedia
| 2019 |
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Computing (specialised) / IEEE Intelligent Systems
| 2019 |
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Software Engineering / ACM queue (FREE)
| 2019 |
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Computing (specialised) / IEEE Pervasive Computing
| 2019 |
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Computing (general) / PhD Theses
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UX & Human Factors / ACM interactions
| 2019 |
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UX & Human Factors / IEEE Computer Graphics & Applications
| 2019 |
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2018 (121)
Computing (general) / IEEE Computer
| 2018 |
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| 2018 |
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Computing (general) / Communications of the ACM
| 2018 |
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Computing (specialised) / IEEE Intelligent Systems
| 2018 |
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UX & Human Factors / ACM interactions
| 2018 |
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UX & Human Factors / IEEE Multimedia
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Computing (general) / ACM Computing Surveys
| 2018 |
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Computing (specialised) / IEEE Internet Computing
| 2018 |
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Computing (specialised) / IEEE Pervasive Computing
| 2018 |
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Software Engineering / IEEE Software
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Computing (general) / PhD Theses
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Computing (specialised) / IEEE Cloud Computing
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Software Engineering / GOTO Conference Videos (FREE)
| 2018 |
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2017 (88)
Computing (general) / Communications of the ACM
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Computing (general) / IEEE Computer
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Software Engineering / IEEE Software
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Enterprise Computing / IEEE IT Professional
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Computing (general) / PhD Theses
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Software Engineering / GOTO Conference Videos (FREE)
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2016 (95)
Computing (general) / IEEE Computer
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Computing (general) / Communications of the ACM
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Software Engineering / IEEE Software
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Computing (specialised) / IEEE Cloud Computing
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Computing (specialised) / IEEE Computing in Science & Engineering
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Enterprise Computing / IEEE IT Professional
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2015 (90)
Computing (general) / Communications of the ACM
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Enterprise Computing / IEEE IT Professional
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Computing (specialised) / IEEE Security & Privacy
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Computing (specialised) / IEEE Internet Computing
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Computing (specialised) / IEEE Intelligent Systems
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Computing (specialised) / IEEE Computing in Science & Engineering
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Computing (general) / IEEE Computer
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UX & Human Factors / IEEE Multimedia
| 2015 |
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Computing (specialised) / IEEE Cloud Computing
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Computing (specialised) / IEEE Pervasive Computing
| 2015 |
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Computing (general) / PhD Theses
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Software Engineering / GOTO Conference Videos (FREE)
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2014 (95)
Computing (general) / Communications of the ACM
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Enterprise Computing / IEEE IT Professional
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Computing (specialised) / IEEE Internet Computing
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Computing (general) / IEEE Computer
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Computing (specialised) / IEEE Intelligent Systems
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UX & Human Factors / IEEE Computer Graphics & Applications
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Software Engineering / IEEE Software
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Computing (general) / PhD Theses
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2013 (85)
Computing (general) / IEEE Computer
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Computing (general) / Communications of the ACM
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Enterprise Computing / IEEE IT Professional
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Computing (specialised) / IEEE Security & Privacy
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Computing (specialised) / IEEE Computing in Science & Engineering
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Software Engineering / IEEE Software
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Computing (specialised) / IEEE Pervasive Computing
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Computing (general) / PhD Theses
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2012 (61)
Computing (general) / IEEE Computer
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Computing (general) / Communications of the ACM
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Computing (specialised) / IEEE Security & Privacy
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UX & Human Factors / IEEE Computer Graphics & Applications
| 2012 |
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Computing (specialised) / IEEE Computing in Science & Engineering
| 2012 |
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Software Engineering / ACM queue (FREE)
| 2012 |
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UX & Human Factors / ACM interactions
| 2012 |
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| 2012 |
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Computing (specialised) / IEEE Pervasive Computing
| 2012 |
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Enterprise Computing / IEEE IT Professional
| 2012 |
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UX & Human Factors / IEEE Multimedia
| 2012 |
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Computing (general) / ACM Computing Surveys
| 2012 |
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Computing (general) / PhD Theses
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2011 (51)
Computing (general) / Communications of the ACM
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UX & Human Factors / ACM interactions
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Computing (specialised) / IEEE Security & Privacy
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Hardware and Microprocessor Systems / IEEE Micro
| 2011 |
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Enterprise Computing / IEEE IT Professional
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| 2011 |
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| 2011 |
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Computing (specialised) / IEEE Pervasive Computing
| 2011 |
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Other / IEEE Annals of the History of Computing
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Computing (general) / PhD Theses
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2010 (55)
Computing (general) / Communications of the ACM
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Software Engineering / ACM queue (FREE)
| 2010 |
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Computing (general) / IEEE Computer
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Enterprise Computing / IEEE IT Professional
| 2010 |
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UX & Human Factors / ACM interactions
| 2010 |
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Computing (specialised) / IEEE Internet Computing
| 2010 |
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Computing (specialised) / IEEE Intelligent Systems
| 2010 |
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Computing (specialised) / IEEE Pervasive Computing
| 2010 |
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Computing (general) / PhD Theses
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2009 (39)
Computing (general) / Communications of the ACM
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Enterprise Computing / IEEE IT Professional
| 2009 |
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UX & Human Factors / IEEE Multimedia
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Computing (specialised) / IEEE Pervasive Computing
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Computing (specialised) / IEEE Security & Privacy
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Computing (general) / PhD Theses
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Computing (specialised) / IEEE Intelligent Systems
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2008 (47)
Computing (general) / Communications of the ACM
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Computing (general) / IEEE Computer
| 2008 |
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Computing (specialised) / IEEE Internet Computing
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Computing (specialised) / IEEE Intelligent Systems
| 2008 |
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| 2008 |
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Hardware and Microprocessor Systems / IEEE Micro
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Computing (specialised) / IEEE Computing in Science & Engineering
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Enterprise Computing / IEEE IT Professional
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Computing (specialised) / IEEE Pervasive Computing
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Computing (general) / PhD Theses
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2007 (38)
Computing (general) / Communications of the ACM
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Enterprise Computing / IEEE IT Professional
| 2007 |
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Computing (specialised) / IEEE Intelligent Systems
| 2007 |
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UX & Human Factors / IEEE Computer Graphics & Applications
| 2007 |
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Computing (general) / IEEE Computer
| 2007 |
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UX & Human Factors / IEEE Multimedia
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Computing (specialised) / IEEE Pervasive Computing
| 2007 |
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| 2007 |
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Computing (specialised) / IEEE Computing in Science & Engineering
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Computing (general) / PhD Theses
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2006 (39)
Software Engineering / ACM queue (FREE)
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Enterprise Computing / IEEE IT Professional
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Computing (specialised) / IEEE Intelligent Systems
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Computing (general) / IEEE Computer
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Computing (specialised) / IEEE Pervasive Computing
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Computing (general) / Communications of the ACM
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Computing (general) / PhD Theses
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Other / IEEE Annals of the History of Computing
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2005 (22)
Computing (general) / Communications of the ACM
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UX & Human Factors / IEEE Computer Graphics & Applications
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Computing (general) / ACM Computing Surveys
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Computing (general) / PhD Theses
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2004 (24)
Computing (general) / Communications of the ACM
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Computing (general) / IEEE Computer
| 2004 |
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Software Engineering / IEEE Software
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Computing (general) / PhD Theses
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2003 (19)
Computing (general) / IEEE Computer
| 2003 |
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Computing (general) / Communications of the ACM
| 2003 |
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UX & Human Factors / IEEE Computer Graphics & Applications
| 2003 |
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Computing (specialised) / IEEE Security & Privacy
| 2003 |
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Software Engineering / IEEE Software
| 2003 |
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Computing (general) / PhD Theses
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2002 (17)
Computing (general) / Communications of the ACM
| 2002 |
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| 2002 |
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Software Engineering / IEEE Software
| 2002 |
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Computing (specialised) / IEEE Internet Computing
| 2002 |
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Computing (specialised) / IEEE Intelligent Systems
| 2002 |
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Computing (specialised) / IEEE Pervasive Computing
| 2002 |
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Computing (general) / PhD Theses
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History
Early Explorations: From Basic Coding to Man-Machine Dialogue (1962-1975)
The earliest period reveals a foundational interest in how computers could interact with and process medical information. In 1962, the focus was squarely on the very practical challenge of transforming patient narratives into structured data, as seen in "Coding of medical case history data for computer analysis." This highlights the initial hurdle: making human-readable medical records machine-interpretable. A companion title, "A missing factor in medical case history?", suggests an early awareness of the nuances and potential shortcomings of converting complex clinical narratives into computable formats.
By 1966, the scope broadened significantly. Titles like "Engineering, medical and scientific applications" and "Man, medicine, mathematics, and machines" indicate a burgeoning interdisciplinary approach, recognizing the necessity of integrating engineering and mathematical principles into medicine. The concept of direct human-computer collaboration emerged with "Man/machine communications in the biological medical research environment," alongside nascent attempts at using computers to directly assist with clinical tasks, such as "Computer aides to medical diagnosis - problems and progress" and "Shock III, a computer system as an aid in the management of critically III patients." This marks a pivotal shift from mere data processing to active computational assistance.
Moving into 1973 and 1975, the idea of computers became more embedded in clinical operations. "Computers in clinical medicine" and "Computerized medical records in multiphasic testing" show a growing adoption of electronic records beyond just coding. Crucially, by 1975, the discussions matured to include public policy implications ("A Problem-List of Public Policy Issues Concerning Computers and Health Care") and the practical status of applications in ambulatory care ("Current Status of Ambulatory Health Care Computer Applications"). The development of systems for medical decision-making, like "Help-A Computer System for Medical Decision Making," and patient management for chronic illness, such as "Computer-Based Aid to Managing Patients with Chronic Illness," underscore a clear continuity in pursuing direct clinical utility. However, the introduction of "Requirements for Computerized Patient Monitoring Systems" also signals an emerging need for standardized, robust functionality for these evolving tools.
The Rise of Expert Systems and Early Imaging (1978-1989)
This period saw a deeper dive into the artificial intelligence capabilities of computers, particularly the development of expert systems, alongside the nascent but impactful emergence of medical imaging.
In 1978 and 1979, the themes revolved around formalizing medical knowledge and creating comprehensive information systems. Titles like "The Use of an Interactive Information Storage and Retrieval System in Medical Research" and "Information Systems for Patient Care" show a continued push for better data organization and accessibility. A significant trend was the focus on representing medical knowledge for machine processing, highlighted by "A Methodology for Machine Representation of Medical Knowledge" and "Medical Guidance and PROMIS." The critique in "Special Feature Computers in Clinical Medicine: a Critique (1978)" also indicates a growing maturity and self-reflection within the field, questioning the effectiveness and challenges of early implementations.
The 1980s cemented these themes and introduced a major new one: imaging. 1980 saw "VM, representing time-dependent relations in a medical setting," emphasizing the complexity of medical data over time. In 1981, "Causal representation of patient illness for electrolyte and acid-base diagnosis" indicates a focus on complex diagnostic reasoning. By 1983, "Digital Picture Archiving and Communication Systems in Medicine - Guest Editors' Introduction" and "Array Processors in Medical Imaging" clearly mark the arrival of digital medical imaging as a distinct and important field.
The mid-to-late 1980s built on these foundations. "Machine learning using fuzzy logic with applications to medicine (1986)" and "Meta description of experimental identification of medical knowledge (1986)" demonstrate the growing sophistication of AI techniques being applied to medical data. "A study of the design, reliability and knowledge structures of a multienvironmental medical expert system (1987)" confirms the continued prominence of expert systems. The decade closed with a surge of titles in 1989 that underscored this growth: "Interactive Visualization of 3D Medical Data," "Three-dimensional medical image analysis," and "Comparative approaches to building expert systems for health care." This era marks a clear shift from primarily text-based data to incorporating visual information and more advanced AI reasoning. The emergence of a "medical information bus" ("The P1073 medical information bus") also hints at the growing need for interconnectedness and standardization.
Connectivity, Multimedia, and Early Security Concerns (1990-1999)
This period is characterized by a significant expansion of computing capabilities beyond just data processing and AI, embracing advanced visualization, networks, and, notably, the first explicit concerns about security and privacy.
The early 1990s continued to push the boundaries of medical imaging and visualization. "Investigation of medical 3D-rendering algorithms (1990)," "Three-Dimensional Medical Imaging: Algorithms and Computer Systems (1991)," and "Graphics applied to medical image registration (1991)" highlight an intense focus on making 3D medical data more useful and interactive. A key continuity was the application of AI and knowledge-based systems, with titles like "Knowledge-guided boundary determination in low-contrast imagery" and "The theory of explanation applied to medical expert systems" (both 1991). The first explicit mention of "Inside Risks: Risks in Medical Electronics (1990)" signifies a crucial new trend: the recognition of cybersecurity and safety concerns in medical technology. Natural language processing also continued to develop ("Building a Speech Interface to a Medical Diagnostic System," 1991).
The mid-1990s brought the burgeoning internet and multimedia into the healthcare sphere. "Network-Compatible Multimedia for Medical Training: MedPics (1994)" and "Multimedia MedNet: A Medical Collaboration and Consultation System (1995)" showcase the shift towards networked, rich media for education and collaboration. The issue of data security became more formalized, as evidenced by "Data security in European healthcare information systems (1995)." The concept of "intelligent patient monitoring" (1995) evolved, now supported by more sophisticated software architectures. The increasing complexity and interconnectedness brought privacy to the forefront, with "Privacy, Information Technology, and Health Care (1997)."
The late 1990s saw the integration of virtual reality ("Medical Applications of Virtual Reality," 1997), widespread adoption of the Internet for knowledge diffusion ("Using the Internet to Improve Knowledge Diffusion in Medicine," 1997), and the continued refinement of image analysis techniques ("Topologically adaptable deformable models for medical image analysis," 1997). The focus expanded to include organizational modeling and knowledge-based scheduling ("Organizational Modeling in CommonKADS: The Emergency Medical Service," 1997; "Knowledge-Based Scheduling Systems in Industry and Medicine," 1997). The term "AI and the Changing Face of Health Care" (1998) suggests AI was moving from niche expert systems to a broader transformative role. By 1999, electronic sharing of patient records and advanced segmentation techniques for medical images were established themes. This period truly marked the transition of medical computing from isolated tools to networked, multimedia-rich environments, with an increasing awareness of associated risks.
Integrated Data, Pervasive Care, and Workflow Optimization (2000-2009)
This decade solidified the move towards comprehensive, networked healthcare systems, with a strong emphasis on data integration, patient monitoring, and optimizing care delivery. Security and privacy remained consistent concerns.
The early 2000s highlighted sophisticated image analysis and data management. "Statistical models in medical image analysis (2000)" and "Curve evolution for medical image segmentation (2000)" show continued refinement in imaging. "Composite and comprehensive multimedia electronic health care records (2000)" indicates the vision for truly integrated digital records. A significant theme was security for these increasingly valuable electronic records: "Security issues for implementation of e-medical records (2001)" and "Protecting Privacy in Remote-Patient Monitoring (2001)." The rise of "Medicine on the Net" (2001) and "Web-Based Digital Medical Images" reflects the internet's growing influence on healthcare delivery. New data analysis techniques like "independent component analysis of biomedical signals" (2001) began to support medical decision-making.
By the mid-2000s, "pervasive healthcare" emerged as a key concept, focusing on continuous monitoring outside traditional clinical settings ("Pervasive Health Care Applications Face Tough Security Challenges," 2002; "Pervasive Healthcare," 2003). There was a clear push for strategic IT applications ("Strategic IT applications in health care," 2002) and improved data exchange between systems ("Information exchange between medical databases through automated identification of concept equivalence," 2002). Titles like "Computer-Assisted Patient Scheduling System (2003)" and "The development of risk adjusted control charts… to monitor the mortality rate of intensive care unit patients (2003)" reveal an increasing interest in operational efficiency and patient safety through data analytics. The idea of "Healthwear: Medical Technology Becomes Wearable (2004)" points to the miniaturization and integration of devices into daily life.
The late 2000s underscored the increasing complexity and scale of healthcare IT. Electronic health records (EHRs) became a central topic, with titles like "A survey and analysis of Electronic Healthcare Record standards (2005)" and "Electronic medical records and computerized physician order entry: Examining factors and methods that foster clinician IT acceptance (2006)." The concepts of "patient safety in wireless medical device networks" (2006) and "coping with defective software in medical devices" (2006) emphasized the critical nature of reliable technology. Agent-based systems for healthcare coordination and monitoring gained traction ("Agent-Based Semantic Service Discovery for Healthcare," 2006; "Multi-Agent Systems Supported Collaboration in Diabetic Healthcare," 2008). The overarching trend was enabling the "21st century health care information technology revolution" (2007) through robust infrastructure, efficient data flow, and ubiquitous access, while grappling with the challenges of data security and interoperability. Operations research models also started gaining prominence for optimizing healthcare logistics ("Applications of Operations Research Models to Problems in Health Care," 2009).
The Era of Big Data, Mobile Health, and Cybersecurity (2010-2014)
This period marked a significant leap in scale and complexity, driven by the proliferation of data, the ubiquitous adoption of mobile technology, and a heightened awareness of the cyber risks associated with interconnected medical systems.
The early 2010s saw a strong emphasis on the "promise and challenge" of "Computers in Patient Care" (2010). Mobile technologies rapidly gained prominence, with titles like "Empowering Healthcare Patients with Smart Technology" (2010) and "Evaluation of using Web 2.0 technologies in diabetes education for adolescent and young patients" (2010). Cybersecurity for medical devices became a critical concern, directly addressed by "Researchers Fight to Keep Implanted Medical Devices Safe from Hackers" (2010). The emergence of "patient-specific modeling" across various medical domains (e.g., "Automated patient-specific modeling of blood flow," 2010; "Patient-specific modeling and quantification of the heart valves," 2010) indicates a shift towards highly individualized care supported by computational tools. Cloud computing also began to feature in healthcare discussions ("A Web 2.0 Model for Patient-Centered Health Informatics Applications," 2010).
Mid-period, the concept of "big data" began to influence healthcare analytics, as hinted by titles focused on "data mining" and "real-time, decision support systems" (2010). The focus on usability in "Electronic medical records: usability challenges and opportunities" (2011) and "Usability Failures and Healthcare Data Hemorrhages" (2011) suggests that while technology was advancing, practical implementation and user experience were becoming recognized pain points. The expansion of connected devices also brought new privacy concerns, such as "Privacy in mobile technology for personal healthcare" (2012).
By 2013 and 2014, the integration of "mobile health" (mHealth) as a transformative force was explicit ("Mobile Health: Revolutionizing Healthcare Through Transdisciplinary Research," 2013). "Leveraging Big Data Analytics to Reduce Healthcare Costs" (2013) highlights the economic imperative driving data-intensive approaches. Patient-centricity remained a core theme, with "User Interfaces for Patient-Centered Communication of Health Status" (2013) and "Using patient data for personalized cancer treatments" (2014). Cybersecurity concerns deepened, extending to "controlling for cybersecurity risks of medical device software" (2013) and the potential for "Attacks in a WBAN system for remote medical monitoring" (2014). The sheer scale of data necessitated "Parallel Algorithms for Medical Informatics on Data-Parallel Many-Core Processors" (2013). This era clearly established the foundation for data-driven, mobile-first healthcare, while simultaneously wrestling with the inherent risks of such widespread connectivity.
The Rise of AI, IoT, and Precision Medicine (2015-2018)
This period is defined by the pervasive integration of Artificial Intelligence (AI) and Machine Learning (ML), the Internet of Things (IoT), and the burgeoning concept of precision medicine, fundamentally reshaping healthcare capabilities.
In 2015, the term "Technological Advances in Medicine: It's Personal" encapsulated a key shift towards individualized care. AI/ML began to take center stage, with titles like "Action Recognition and Prediction with Applications to Medical Diagnosis" and "Developing and Integrating Computer-Aided Diagnostic Tools into Clinical Medicine" underscoring its growing utility. The IoT gained explicit recognition as a backbone for healthcare, exemplified by "Improving Healthcare for Populations: Building Smart and Integrated Remote Health Monitoring Systems" and "An Internet of Things for Healthcare." Data security remained a persistent concern, now extending to "mobile and cloud frontiers in healthcare" and "security challenges for medical devices." The concept of "Whole Genome Sequencing: Revolutionary Medicine or Privacy Nightmare?" highlights the dual promise and challenge of data-rich precision medicine.
By 2016, AI's role deepened, with "Machine learning for medical diagnostics: techniques for feature extraction, classification, and evaluation" and the introduction of "deep learning methods for medical image processing and analysis." The security narrative matured to include "a brief chronology of medical device security" and "High-Confidence Medical Device Software and Systems." The vision for "Autonomic and Cognitive IoT Systems" for patient management emerged. Precision medicine solidified as a key theme, with "Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine." Collaboration and interoperability across patient care models also received significant attention.
The years 2017 and 2018 saw the widespread adoption and diversification of AI and deep learning across various medical applications. "Deep Learning in Medicine" (2018) became a standalone subject, indicating its maturity. "Intelligent systems for personalized genomic medicine" (2017) and "Leveraging knowledge networks for precision medicine" (2018) showcase the convergence of AI with genomics. Blockchain technology entered the conversation, particularly for secure electronic health records ("Blockchain in Healthcare," 2018). Wearable technologies became more integrated ("Wearables and Medical Interoperability," 2018). The emphasis on "patient-specific" approaches intensified across imaging, biomechanical models, and even rehabilitation. Security and privacy became more complex, with discussions on "Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems" (2018) and "Privacy-Enhancing Technologies for Medical and Genomic Data." This period truly cemented AI and IoT as fundamental drivers of innovation, moving towards a highly personalized and interconnected healthcare landscape, while simultaneously grappling with data trust and security at an unprecedented scale.
Deep Learning, Explainable AI, and Real-World Challenges (2019-2021)
This recent period is marked by the pervasive dominance of deep learning, a growing emphasis on explainability and human-centric AI, and the direct influence of global health challenges on technological development.
In 2019, "Deep Learning Based Medical Image Analysis with Limited Data" and "Hierarchical Deep Learning for Disease Identification in High-Resolution Medical Imaging" show deep learning's continued advancement, even addressing data scarcity. The imperative for "Explainable Machine Learning for Science and Medicine" emerged, recognizing the need for transparency in AI-driven decisions. The focus on patient experience expanded beyond data to include understanding "patient experience from online medium" and "promoting credibility, belonging, and participation in medical support communities." Cybersecurity remained paramount, with titles like "a machine learning framework for securing patient records" and "Medical Device Security Through Hardware Signatures." The development of "patient-specific models" was a strong continuity, now frequently coupled with deep learning.
The year 2020 saw deep learning applied to even more specialized tasks, such as "Robust Medical Image Registration and Motion Modeling based on Machine Learning" and "Deep Neural Networks for the segmentation and classification in Medical Imaging." The concept of "Digital healthcare" was widely discussed, expanding geographically ("Digital healthcare in Latin America," "Digital healthcare across Oceania"). The "Internet of Medical Things" (IoMT) gained explicit recognition as a distinct domain. The need for "Human-Centered Machine Learning for Healthcare" became a more prominent theme, alongside the practicalities of improving healthcare management through simulation and optimization. The global context, notably the COVID-19 pandemic, likely spurred interest in "real-time patient monitoring" and "telemedicine infrastructure."
In 2021, deep learning's reach broadened further, encompassing "Multimodal Representation Learning for Medical Image Analysis" and "Deep Learning in Medical Image Analysis." The push for "precision medicine" continued, increasingly leveraging "Machine Learning approaches in Predictive Medicine using Electronic Health Records data." Ethical considerations for AI became more explicit, as seen in "The Ten Commandments of Ethical Medical AI" and "Privacy and transparency in learning systems for healthcare." "Blockchain Innovations for Healthcare" continued to be explored for secure data management. The emphasis on "human-AI interfaces to support explainability and causability in medical AI" highlights a critical shift towards designing AI that clinicians and patients can understand and trust. The practical implementation of remote monitoring and telehealth, potentially accelerated by the pandemic, also featured prominently ("PIMAP: A System Framework For Patient Monitoring," "Smart Multimodal Telehealth-IoT System for COVID-19 Patients"). This period solidified deep learning as a core technology while bringing ethical design, user trust, and real-world applicability to the forefront of medical AI development.
Advanced AI, Digital Ecosystems, and Trustworthy Healthcare (2022-Present)
The most recent period showcases a mature and sophisticated integration of AI and digital technologies into all facets of healthcare, with a strong focus on advanced machine learning techniques, comprehensive digital ecosystems, and robust ethical and security frameworks.
In 2022, the landscape of AI in healthcare became even more specialized, with "Deep Learning for Medical Anomaly Detection" and "User-Centered Deep Learning for Medical Image Analysis" indicating a focus on specific, actionable applications. The concept of "Images in Space and Time: Real Big Data in Healthcare" points to the increasing scale and complexity of medical datasets. "Decentralized Machine Learning for Intelligent Health-Care Systems on the Computing Continuum" hints at distributed AI processing. The critical need for trust and ethical implementation is highlighted by "Reinforcing machine learning best practices in medicine and the life sciences" and "Accuracy Medical Image Segmentation with Limited Annotations," which addresses practical challenges to AI robustness. Patient-centricity remained a strong theme, with titles like "Patient-centric approach to maximize CPAP therapy acceptance." The importance of "data quality trust" and "provenance-based data quality assessment" reflects the growing understanding that AI is only as good as its input data.
Looking at 2023 and 2024, the themes become even more refined. "Federated Learning for Smart Healthcare" and "Reinforcement Learning in Healthcare" point to advanced, collaborative AI models. "Generative Adversarial Network in Medical Image Analysis" indicates a new frontier in synthetic data creation for training AI, potentially addressing privacy concerns. The focus on "Explainable AI Healthcare predictive Models" and "Interpretable Machine Learning With Medical Applications" is paramount, emphasizing AI transparency for clinical adoption. The "Internet of Healthcare Things – A Platform Approach" (2017, but a strong continuation and maturation into this period) is seen with "Container-Based Data Pipelines on the Computing Continuum for Remote Patient Monitoring" and the explicit "Internet of Medical Things" (IoMT). Regulatory compliance for AI-based medical devices emerged as a key consideration ("Toward a Regulatory-Compliant Lifecycle for Artificial-Intelligence-Based Medical Devices in the European Union," 2024). Blockchain continued to be explored for patient-centric ecosystems and data sharing ("Blockchain Adoption in Healthcare," 2023). Virtual reality and extended reality (XR) are highlighted for training and teleconsultation ("Immersive Medical VR Training Simulators with Haptic Feedback," 2024). The pervasive nature of AI and digital health now also addresses broader societal impacts, such as "AI and Big Data in Health: Boosting Reliability and Efficiency in Predictive Healthcare Models" and "Machine Learning Approaches for Equitable Healthcare." This period solidifies the move towards highly intelligent, interconnected, and ethically-driven digital health ecosystems, pushing the boundaries of AI while focusing intently on trustworthiness, patient safety, and broader societal impact.