Artificial Intelligence in Healthcare (Review)

Overview

Journal Biomed Rep

Specialty Biochemistry

Date 2024 Nov 25

PMID 39583770

Authors

Abdul-Mohsen G Alhejaily

Affiliations

Soon will be listed here.

Abstract

The potential of artificial intelligence (AI) to significantly transform numerous aspects of contemporary civilization is substantial. Advancements in research show an increasing interest in creating AI solutions in the healthcare sector. This interest is driven by the broad spectrum and extensive nature of easily accessible patient data-including medical imaging, digitized data collection, and electronic health records - and by the ability to analyze and interpret complex data, facilitating more accurate and timely diagnoses. This review's goal is to provide a comprehensive overview of the advancements achieved by AI in healthcare, to elucidate the present state of AI in enhancing the healthcare system and improving the quality and efficiency of healthcare decision making, and to discuss selected medical applications of AI. Furthermore, the barriers and constraints that may impede the use of AI in healthcare are outlined, and the potential future directions of AI-augmented healthcare systems are discussed.

References

Giger M . Machine Learning in Medical Imaging. J Am Coll Radiol. 2018; 15(3 Pt B):512-520. DOI: 10.1016/j.jacr.2017.12.028. View

Litjens G, Sanchez C, Timofeeva N, Hermsen M, Nagtegaal I, Kovacs I . Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis. Sci Rep. 2016; 6:26286. PMC: 4876324. DOI: 10.1038/srep26286. View

Rajpurkar P, Chen E, Banerjee O, Topol E . AI in health and medicine. Nat Med. 2022; 28(1):31-38. DOI: 10.1038/s41591-021-01614-0. View

Campanella G, Hanna M, Geneslaw L, Miraflor A, Silva V, Busam K . Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nat Med. 2019; 25(8):1301-1309. PMC: 7418463. DOI: 10.1038/s41591-019-0508-1. View

Goirand M, Austin E, Clay-Williams R . Implementing Ethics in Healthcare AI-Based Applications: A Scoping Review. Sci Eng Ethics. 2021; 27(5):61. DOI: 10.1007/s11948-021-00336-3. View

Abramoff M, Lavin P, Birch M, Shah N, Folk J . Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ Digit Med. 2019; 1:39. PMC: 6550188. DOI: 10.1038/s41746-018-0040-6. View

Senaras C, Khan Niazi M, Lozanski G, Gurcan M . DeepFocus: Detection of out-of-focus regions in whole slide digital images using deep learning. PLoS One. 2018; 13(10):e0205387. PMC: 6201886. DOI: 10.1371/journal.pone.0205387. View

Choi K . [Integrating Artificial Intelligence Into Healthcare Research]. Hu Li Za Zhi. 2020; 67(5):12-18. DOI: 10.6224/JN.202010_67(5).03. View

Veta M, van Diest P, Kornegoor R, Huisman A, Viergever M, Pluim J . Automatic nuclei segmentation in H&E stained breast cancer histopathology images. PLoS One. 2013; 8(7):e70221. PMC: 3726421. DOI: 10.1371/journal.pone.0070221. View

10.

Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S . Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2018; 2(4):230-243. PMC: 5829945. DOI: 10.1136/svn-2017-000101. View

11.

Yu K, Beam A, Kohane I . Artificial intelligence in healthcare. Nat Biomed Eng. 2019; 2(10):719-731. DOI: 10.1038/s41551-018-0305-z. View

12.

Davenport T, Kalakota R . The potential for artificial intelligence in healthcare. Future Healthc J. 2019; 6(2):94-98. PMC: 6616181. DOI: 10.7861/futurehosp.6-2-94. View

13.

Torkamani A, Andersen K, Steinhubl S, Topol E . High-Definition Medicine. Cell. 2017; 170(5):828-843. PMC: 5714316. DOI: 10.1016/j.cell.2017.08.007. View

14.

Alowais S, Alghamdi S, Alsuhebany N, Alqahtani T, Alshaya A, Almohareb S . Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ. 2023; 23(1):689. PMC: 10517477. DOI: 10.1186/s12909-023-04698-z. View

15.

Weng S, Reps J, Kai J, Garibaldi J, Qureshi N . Can machine-learning improve cardiovascular risk prediction using routine clinical data?. PLoS One. 2017; 12(4):e0174944. PMC: 5380334. DOI: 10.1371/journal.pone.0174944. View

16.

Fogel A, Kvedar J . Artificial intelligence powers digital medicine. NPJ Digit Med. 2019; 1:5. PMC: 6548340. DOI: 10.1038/s41746-017-0012-2. View

17.

Muthukrishnan N, Maleki F, Ovens K, Reinhold C, Forghani B, Forghani R . Brief History of Artificial Intelligence. Neuroimaging Clin N Am. 2020; 30(4):393-399. DOI: 10.1016/j.nic.2020.07.004. View

18.

Akselrod-Ballin A, Chorev M, Shoshan Y, Spiro A, Hazan A, Melamed R . Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms. Radiology. 2019; 292(2):331-342. DOI: 10.1148/radiol.2019182622. View

19.

Aung Y, Wong D, Ting D . The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare. Br Med Bull. 2021; 139(1):4-15. DOI: 10.1093/bmb/ldab016. View

20.

Esteva A, Robicquet A, Ramsundar B, Kuleshov V, DePristo M, Chou K . A guide to deep learning in healthcare. Nat Med. 2019; 25(1):24-29. DOI: 10.1038/s41591-018-0316-z. View