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A systematic survey of computer-aided diagnosis in medicine: Past and present developments
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“Models that may perform well during development can degrade in real-world settings due to dataset drift across diverse sites, devices, and populations15–18.”
From What the AI era doctor should know: a scoping review of proposed artificial intelligence competencies for medical education (2026) · cites this paper as [15]
Citations
Cites
Items 201–254 of 254
Comparison of Two Educational Interventions on Pediatric Resident Auscultation Skills
Mahnke, C. B., Nowalk, A. J., Hofkosh, D., Zuberbuhler, J. R., & Law, Y. M. (2004) · PEDIATRICS · doi:10.1542/peds.113.5.1331 · Cited by 66
Correlating electronic health record concepts with healthcare process events
Hripcsak, G. M., & Albers, D. J. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001922 · Cited by 63
Thung, K.-H., Yap, P.-T., & Shen, D. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-67558-9_19 · Cited by 63
Chest pathology identification using deep feature selection with non-medical training
Bar, Y., Diamant, I., Wolf, L., Lieberman, S., Konen, E., & Greenspan, H. K. (2016) · Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization · doi:10.1080/21681163.2016.1138324 · Cited by 62
Medical diagnosis with the aid of using fuzzy logic and intuitionistic fuzzy logic
Das, S., Guha, D., & Dutta, B. (2016) · Applied Intelligence · doi:10.1007/s10489-016-0792-0 · Cited by 62
Foundations of artificial intelligence
BARKER, P. G. (1993) · Engineering Applications of Artificial Intelligence · doi:10.1016/0952-1976(93)90045-y · Cited by 59
Croisille, P., Souto, M., Cova, M., Wood, S., Afework, Y., Kuhlman, J. E., & Zerhouni, E. A. (1995) · Radiology · doi:10.1148/radiology.197.2.7480683 · Cited by 58
Patidar, S., & Pachori, R. B. (2013) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2013.05.004 · Cited by 58
Challenges for computer-aided diagnosis for CT colonography
Summers, R. M. (2002) · Abdominal Imaging · doi:10.1007/s00261-001-0168-7 · Cited by 58
Standardizing predictive values in diagnostic imaging research
Heston, T. F. (2011) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22466 · Cited by 53
Digital Electronic Computers in Biomedical Science
Ledley, R. S. (1959) · Science · doi:10.1126/science.130.3384.1225 · Cited by 53
Interactive learning of monotone Boolean functions
Kovalerchuk, B., Triantaphyllou, E., Deshpande, A. S., & Vityaev, E. E. (1996) · Information Sciences · doi:10.1016/0020-0255(96)00082-5 · Cited by 49
Self-citationThe Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining
Pham, H. N. A., & Triantaphyllou, E. (2007) · Springer eBooks · doi:10.1007/978-0-387-69935-6_16 · Cited by 47
Self-citationClinically Missed Cancer: How Effectively Can Radiologists Use Computer-Aided Detection?
Nishikawa, R. M., Schmidt, R. A., Linver, M. N., Edwards, A. V., Papaioannou, J., & Stull, M. A. (2012) · American Journal of Roentgenology · doi:10.2214/ajr.11.6423 · Cited by 47
The Accuracy of Mammographic Interpretation
Kopans, D. B. (1994) · New England Journal of Medicine · doi:10.1056/nejm199412013312213 · Cited by 46
Computer-aided Detection: There Is No Free Lunch
D’Orsi, C. J. (2001) · Radiology · doi:10.1148/radiol.2213011476 · Cited by 45
Winters-Miner, L. A., Bolding, P. S., Hilbe, J. M., Goldstein, M., Hill, T., Nisbet, R., Walton, N., & Miner, G. D. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-411643-6.00003-x · Cited by 41
Computer‐aided pattern classification system for dermoscopy images
Abbas, Q., Celebi, M. E., & Fondón, I. (2011) · Skin Research and Technology · doi:10.1111/j.1600-0846.2011.00562.x · Cited by 40
Overdiagnosed: Making People Sick in the Pursuit of Health
Welch, H. G., Schwartz, L., & and Woloshin, S. (2011) · DigitalGeorgetown (Georgetown University Library) · Cited by 40
Biomedical Signal Analysis: Contemporary Methods and Applications
Theis, F. J., & Meyer‐Baese, A. (2010) · Cited by 39
Beyond focused assessment with sonography for trauma
Matsushima, K., & Frankel, H. L. (2011) · Current Opinion in Critical Care · doi:10.1097/mcc.0b013e32834be582 · Cited by 39
Merck Manual : for health care professionals
Porter, R. S., & Kaplan, J. L. (2011) · Cited by 38
Larson, W. (2011) · British Film Institute eBooks · doi:10.1007/978-1-84457-580-0_13 · Cited by 38
Shape-based kidney detection and segmentation in three-dimensional abdominal ultrasound images
Marsousi, M., Plataniotis, K. N., & Stergiopoulos, S. (2014) · doi:10.1109/embc.2014.6944227 · Cited by 36
Eugene Charniak, D. (2019) · Cited by 36
Sethi, I. K. (2001) · Massive computing · doi:10.1007/978-1-4757-4911-3_1 · Cited by 35
Pham, H. N. A., & Triantaphyllou, E. (2008) · Springer eBooks · doi:10.1007/978-3-540-79187-4_2 · Cited by 34
Self-citationBella, G. D., Minutoli, F., Piaggi, P., Casale, M., Mazzeo, A. T., Zito, C., Oreto, G., Baldari, S., Vita, G., Pingitore, A., et al. (2015) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2015.07.008 · Cited by 34
Failure to Return for HIV Test Results: A Pilot Study of Three Community Testing Sites
Grusky, O., Roberts, K. J., & Swanson, A. (2007) · Journal of the International Association of Physicians in AIDS Care · doi:10.1177/1545109706297530 · Cited by 32
Bhooshan, N., Giger, M. L., Medved, M., Li, H., Wood, A. M., Yuan, Y., Li, L., Marquez, A., Karczmar, G. S., & Newstead, G. M. (2013) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24145 · Cited by 26
Fractal dimension as a feature for adaptive electroencephalogram segmentation in epilepsy
Kirlangic, M. E., Perez, D., Kudryavtseva, S., Griessbach, G., Henning, G., & Ivanova, G. (2005) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2001.1020511 · Cited by 26
Neural networks at the crossroads: caution ahead.
Gurney, J. W. (1994) · Radiology · doi:10.1148/radiology.193.1.8090906 · Cited by 24
Weighted relaxed support vector machines
Şeref, O., Razzaghi, T., & Xanthopoulos, P. (2014) · Annals of Operations Research · doi:10.1007/s10479-014-1711-6 · Cited by 21
Intuitionistic fuzzy C-regression by using least squares support vector regression
Lin, K.-P., Chang, H.-F., Chen, T.-L., Lu, Y., & Wang, C.-H. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.07.040 · Cited by 21
High performance heart sound segmentation algorithm based on Matching Pursuit
Nieblas, C. I., Alonso, M., Conte, R., & Villarreal‐Reyes, S. (2013) · IEEE Digital Signal Processing Workshop and IEEE Signal Processing Education Workshop (DSP/SPE) · doi:10.1109/dsp-spe.2013.6642572 · Cited by 20
How do we manage overdiagnosis/overtreatment in breast screening?
Wallis, M. (2017) · Clinical Radiology · doi:10.1016/j.crad.2017.09.016 · Cited by 19
Wang, L. V. (2014) · Scholarpedia · doi:10.4249/scholarpedia.10278 · Cited by 19
The Reliability Issue of Computer-Aided Breast Cancer Diagnosis
Kovalerchuk, B., Triantaphyllou, E., Ruiz, J. F., Torvik, V. I., & Vityaev, E. E. (2000) · Computers and Biomedical Research · doi:10.1006/cbmr.2000.1546 · Cited by 19
Self-citationThomaz, R. L., Carneiro, P. C., & Patrocínio, A. C. (2017) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2254633 · Cited by 18
Morra, L., Delsanto, S., & Correale, L. (2019) · CRC Press eBooks · doi:10.1201/9780367229184-2 · Cited by 18
COMPUTERS IN MEDICINE AND BIOLOGY
Weinrauch, H. (1959) · JAMA · doi:10.1001/jama.1959.03000200038008 · Cited by 17
Fast Imbalanced Classification of Healthcare Data with Missing ValuesPreprint
Razzaghi, T., Roderick, O., Safro, I., & Marko, N. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1503.06250 · Cited by 17
Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images
Deng, H., Deng, W., Sun, X., Ye, C., & Zhou, X. H. (2016) · Scientific Reports · doi:10.1038/srep35760 · Cited by 15
Real-Time Visualization of 4D Cardiac MR Images Using Graphics Processing Units
Zhang, Q., Eagleson, R. A., & Peters, T. M. (2006) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2006.1624923 · Cited by 14
Decision support in heart failure through processing of electro- and echocardiograms
Chiarugi, F., Colantonio, S., Emmanouilidou, D., Martinelli, M., Moroni, D., & Salvetti, O. (2010) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2010.05.001 · Cited by 13
Knowledge based expert systems for medical diagnosis
Torasso, P. (1985) · Statistics in Medicine · doi:10.1002/sim.4780040311 · Cited by 13
Consistency of rule-based expert systems
Bezem, M. (2005) · Springer eBooks · doi:10.1007/bfb0012830 · Cited by 11
Sidetracked at the crossroads.
Boone, J. M. (1994) · Radiology · doi:10.1148/radiology.193.1.8090909 · Cited by 10
A low-complex multi-channel methodology for noise detection in phonocardiogram signals
Nunes, D., Leal, A., Couceiro, R., Henriques, J. M. O., Mendes, L. G. A., Carvalho, P., & Teixeira, C. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319743 · Cited by 10
Digital (r)evolution in radiology : bridging the future of health care
Hrudy, W. (2010) · Springer eBooks · Cited by 9
The paediatrician and cardiac auscultation
Roy, D. L. (2003) · Paediatrics & Child Health · doi:10.1093/pch/8.9.561 · Cited by 9
Smith, R. A., Brawley, O. W., & Wender, R. C. (2017) · doi:10.1002/9781119468868.ch11 · Cited by 3
Miller, K., Capan, M., Wu, P., Jackson, E. V., & Arnold, R. C. (2015) · Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care · doi:10.1177/2327857915041032 · Cited by 2
Effect of Mixed Anesthesia on Cardiac Function by Phonocardiogram
Han, H., Hongmei, Yan, Y., Xin-Chuan, Nie, W., & Qing, Q. (2008) · 中国电子科技:英文版 · Cited by 2
Research works printed but not linked: 6
- Beers, 1999, 17, 39
- Bramer, 1982, A survey and critical review of expert systems research, 3
- Lalkhen, 2008, Clinical tests: Sensitivity and specificity. Continuing education in Anaesthesia, Critical Care & Pain, 8, 221
- Szklo, 2014, Epidemiology
- Tan, 2006, Data mining introduction
- Vandenberg, 1960, Medical diagnosis by computer: Recent attempts and outlook for the future, Behavioral Science, 5, 170
Cited by
Sorted by citations
Alshmrani, G. M., Ni, Q., Jiang, R., Pervaiz, H., & Elshennawy, N. M. (2022) · Alexandria Engineering Journal · doi:10.1016/j.aej.2022.10.053 · Cited by 359
Machine learning in clinical decision making
Adlung, L., Cohen, Y., Mor, U., & Elinav, E. (2021) · Med · doi:10.1016/j.medj.2021.04.006 · Cited by 321
Machine Learning for Lung Cancer Diagnosis, Treatment, and Prognosis
Li, Y., Xin, W., Yang, P., Jiang, G., & Luo, Y. (2022) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2022.11.003 · Cited by 287
Brain-Computer Interface: Advancement and Challenges
Mridha, M. F., Das, S. C., Kabir, M. M., Lima, A. A., Islam, M. R., & Watanobe, Y. (2021) · Sensors · doi:10.3390/s21175746 · Cited by 288
Machine Learning Tools for Long-Term Type 2 Diabetes Risk Prediction
Fazakis, N., Kocsis, O., Dritsas, E., Alexiou, S., Fakotakis, N., & Moustakas, K. (2021) · IEEE Access · doi:10.1109/access.2021.3098691 · Cited by 172
Metadata
- Authors
- Yanase, J., & Triantaphyllou, E.
- Affiliations
- Louisiana State University (US)
- Corresponding author
- Triantaphyllou, Evangelos
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 138
- Pages
- 112821
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2959687571
- Cited by
- 303
- References
- 265
- Citations by year
- 2026: 15 · 2025: 43 · 2024: 51 · 2023: 64 · 2022: 63 · 2021: 46 · 2020: 18 · 2019: 3
- FWCI
- 35.61
- Type
- journal article
- Language
- en
- Open access
- Locations
- Expert Systems with Applications (publishedVersion)
- Civil War Book Review (submittedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Keywords
- computer-aided diagnosis, expert systems, intelligent systems, medical data processing, clinical decision-making
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