The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Artificial Intelligence in Medicine: Where Are We Now?
Abstract
Artificial intelligence in medicine has made dramatic progress in recent years. However, much of this progress is seemingly scattered, lacking a cohesive structure for the discerning observer. In this article, we will provide an up-to-date review of artificial intelligence in medicine, with a specific focus on its application to radiology, pathology, ophthalmology, and dermatology. We will discuss a range of selected papers that illustrate the potential uses of artificial intelligence in a technologically advanced future.
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Citations
Cites
The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary
Louis, D. N., Perry, A., Reifenberger, G., von Deimling, A., Figarella-Branger, D., Cavenee, W. K., Ohgaki, H., Wiestler, O. D., Kleihues, P., & Ellison, D. W. (2016) · Acta Neuropathologica · doi:10.1007/s00401-016-1545-1 · Cited by 15,657
Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature · doi:10.1038/nature21056 · Cited by 14,362
High-performance medicine: the convergence of human and artificial intelligence
Topol, E. J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0300-7 · Cited by 10,450
Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., Cuadros, J., et al. (2016) · JAMA · doi:10.1001/jama.2016.17216 · Cited by 7,697
Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., & Summers, R. M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.369 · Cited by 4,616
The potential for artificial intelligence in healthcare
Davenport, T., & Kalakota, R. (2019) · Future Healthcare Journal · doi:10.7861/futurehosp.6-2-94 · Cited by 3,800
Ehteshami Bejnordi, B., Veta, M., Johannes van Diest, P., van Ginneken, B., Karssemeijer, N., Litjens, G., van der Laak, J. A. W. M., and the CAMELYON16 Consortium, Hermsen, M., Manson, Q. F., et al. (2017) · JAMA · doi:10.1001/jama.2017.14585 · Cited by 3,293
DNA methylation-based classification of central nervous system tumours
Capper, D., Jones, D. T. W., Sill, M., Hovestadt, V., Schrimpf, D., Sturm, D., Koelsche, C., Sahm, F., Chavez, L., Reuss, D. E., et al. (2018) · Nature · doi:10.1038/nature26000 · Cited by 3,033
Coudray, N., Ocampo, P. S., Sakellaropoulos, T., Narula, N., Snuderl, M., Fenyö, D., Moreira, A. L., Razavian, N., & Tsirigos, A. (2018) · Nature Medicine · doi:10.1038/s41591-018-0177-5 · Cited by 2,930
Clinically applicable deep learning for diagnosis and referral in retinal disease
De Fauw, J., Ledsam, J. R., Romera-Paredes, B., Nikolov, S., Tomasev, N., Blackwell, S., Askham, H., Glorot, X., O’Donoghue, B., Visentin, D., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0107-6 · Cited by 2,639
Cited by
Artificial intelligence and computational pathology
Cui, M., & Zhang, D. Y. (2021) · Laboratory Investigation · doi:10.1038/s41374-020-00514-0 · Cited by 544
A survey on deep learning in medicine: Why, how and when?
Piccialli, F., Somma, V. D., Giampaolo, F., Cuomo, S., & Fortino, G. (2021) · Information Fusion · doi:10.1016/j.inffus.2020.09.006 · Cited by 348
Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective
Jutzi, T. B., Krieghoff-Henning, E. I., Holland-Letz, T., Utikal, J. S., Hauschild, A., Schadendorf, D., Sondermann, W., Fröhling, S., Hekler, A., Schmitt, M., et al. (2020) · Frontiers in Medicine · doi:10.3389/fmed.2020.00233 · Cited by 196
Babel, A., Taneja, R., Mondello Malvestiti, F., Monaco, A., & Donde, S. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.669869 · Cited by 199
Integration of artificial intelligence into nursing practice
Abuzaid, M. M., Elshami, W., & Fadden, S. M. (2022) · Health and Technology · doi:10.1007/s12553-022-00697-0 · Cited by 172
Metadata
- Authors
- Kulkarni, S., Seneviratne, N., Baig, M. S., & Khan, A. H. A.
- Venue
- Academic Radiology
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 27
- Issue
- 1
- Pages
- 62-70
- ISSN
- 1076-6332 (ISSN-L)
- OpenAlex
- W2981092563
- Cited by
- 282
- References
- 52
- FWCI
- 7.06
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Artificial Intelligence in Medicine: Where Are We Now? https://app.cochat.ai/papers/10.1016/j.acra.2019.10.001
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- Kulkarni, S., Seneviratne, N., Baig, M. S., & Khan, A. H. A. (2020). Artificial Intelligence in Medicine: Where Are We Now? Academic Radiology. https://doi.org/10.1016/j.acra.2019.10.001
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
