Advancing Healthcare Through Data-Driven Medicine and Artificial Intelligence.
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AI/ML techniques have been widely applied in healthcare to generate insights from massive amounts of data.
“AI/ML techniques have been widely applied in healthcare to generate insights from massive amounts of data [20–22]”
From Artificial intelligence and machine learning in mobile apps for mental health: A scoping review (2022) · cites this paper as [20]
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Artificial intelligence and machine learning in mobile apps for mental health: A scoping review
Milne-Ives, M., Selby, E., Inkster, B., Lam, C., & Meinert, E. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000079 · Cited by 68 · see citing works
Alolayyan, M. N., Alyahya, M. S. I., AlAlawin, A. H., Shoukat, A., & Nusairat, F. T. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e05040 · Cited by 58 · see citing works
Design Foundations for AI Assisted Decision Making: A Self Determination Theory Approach
De Vreede, T., Raghavan, M., & De Vreede, G.-J. (2021) · Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.24251/hicss.2021.019 · Cited by 42 · see citing works
Bingley, W., Haslam, S. A., Steffens, N. K., Gillespie, N. A., Worthy, P., Curtis, C., Lockey, S., Bialkowski, A., Ko, R. K. L., & Wiles, J. (2023) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2023.101025 · Cited by 22 · see citing works
Rony, M. K. K., Akter, K., Debnath, M., Rahman, M. M., Johra, F. T., Akter, F., Das, D. C., Mondal, S., Das, M., Uddin, M. J., et al. (2024) · Journal of Medicine Surgery and Public Health · doi:10.1016/j.glmedi.2024.100113 · Cited by 25 · see citing works
Davis, V. H., Qiang, J. R., Adekoya, I., Howse, D., Seshie, A. Z., Kosowan, L., Delahunty‐Pike, A., Abaga, E., Cooney, J., Robinson, M., et al. (2025) · Journal of Medical Internet Research · doi:10.2196/52244 · Cited by 14 · see citing works
Nogaroli, R., & Júnior, J. L. D. M. F. (2023) · Law, governance and technology series · doi:10.1007/978-3-031-41264-6_12 · Cited by 5 · see citing works
INTELIGÊNCIA ARTIFICIAL E BIG DATA NO DIAGNÓSTICO E TRATAMENTO DA COVID-19 NA AMÉRICA LATINA
Neto, M. K., Silva, R. D. G., & Nogaroli, R. (2020) · Revista Brasileira de Direitos Fundamentais & Justiça · doi:10.30899/dfj.v0i0.974 · Cited by 3 · see citing works
Eine intelligente Gesundheitsversorgung
Otto, C. (2021) · Recht Innovativ · doi:10.1007/s43442-021-0061-5
Next‐Generation Distributed Computing for Cancer Detection
Gupta, K. K., Dhanda, N., & Kumar, N. (2024) · doi:10.1002/9781394205127.ch7
da Silva, M. G., Mohsen, Y. I., Pinheiro, V. D. O., Fausto, I. R. D. S., Filho, P. F., & Calado, R. D. (2025) · IEEE International Conference on Industry Applications · doi:10.1109/induscon66435.2025.11241259
- Authors
- Balicer, R. D., & Cohen-Stavi, C.
- Affiliations
- Ben-Gurion University of the Negev (IL)
- Clalit Health Services (IL)
- Corresponding author
- Balicer, Ran D.
- Venue
- Healthcare and Artificial Intelligence
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 9-15
- OpenAlex
- W3012069423
- Cited by
- 11
- References
- 0
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 2 · 2022: 1 · 2021: 2 · 2020: 2
- FWCI
- 1.06
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Keywords
- data-driven medicine, artificial intelligence in healthcare, health system challenges, population aging, chronic disease, health system capacity
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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