Machine Learning in Healthcare

Overview

Journal Curr Genomics

Publisher Bentham Science Publishers

Date 2022 Mar 11

PMID 35273459

Authors

Hafsa Habehh

Suril Gohel

Affiliations

Soon will be listed here.

Abstract

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few. Although, skepticism remains regarding the practical application and interpretation of results from ML-based approaches in healthcare settings, the inclusion of these approaches is increasing at a rapid pace. Here we provide a brief overview of machine learning-based approaches and learning algorithms including supervised, unsupervised, and reinforcement learning along with examples. Second, we discuss the application of ML in several healthcare fields, including radiology, genetics, electronic health records, and neuroimaging. We also briefly discuss the risks and challenges of ML application to healthcare such as system privacy and ethical concerns and provide suggestions for future applications.

Citing Articles

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PLOD3 as a novel oncogene in prognostic and immune infiltration risk model based on multi-machine learning in cervical cancer.

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Predicting triage of pediatric patients in the emergency department using machine learning approach.

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An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation.

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The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review.

Elvas L, Almeida A, Ferreira J JMIR Med Inform. 2025; 13:e64349.

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References

Levine D, Linder J, Landon B . Characteristics of Americans With Primary Care and Changes Over Time, 2002-2015. JAMA Intern Med. 2019; 180(3):463-466. PMC: 6990950. DOI: 10.1001/jamainternmed.2019.6282. View

Esteva A, Kuprel B, Novoa R, Ko J, Swetter S, Blau H . Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017; 542(7639):115-118. PMC: 8382232. DOI: 10.1038/nature21056. View

Pan X, Zuallaert J, Wang X, Shen H, Campos E, Marushchak D . ToxDL: deep learning using primary structure and domain embeddings for assessing protein toxicity. Bioinformatics. 2020; 36(21):5159-5168. DOI: 10.1093/bioinformatics/btaa656. View

Lee J, Jeong E, Lee J, Jung M, Shin E, Kim Y . Directed evolution of CRISPR-Cas9 to increase its specificity. Nat Commun. 2018; 9(1):3048. PMC: 6078992. DOI: 10.1038/s41467-018-05477-x. View

Finlayson S, Bowers J, Ito J, Zittrain J, Beam A, Kohane I . Adversarial attacks on medical machine learning. Science. 2019; 363(6433):1287-1289. PMC: 7657648. DOI: 10.1126/science.aaw4399. View

Nguyen B, Pham H, Tran H, Nghiem N, Nguyen Q, Do T . Predicting the onset of type 2 diabetes using wide and deep learning with electronic health records. Comput Methods Programs Biomed. 2019; 182:105055. DOI: 10.1016/j.cmpb.2019.105055. View

Gaonkar B, Davatzikos C . Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification. Neuroimage. 2013; 78:270-83. PMC: 3767485. DOI: 10.1016/j.neuroimage.2013.03.066. View

Alqudah A . AOCT-NET: a convolutional network automated classification of multiclass retinal diseases using spectral-domain optical coherence tomography images. Med Biol Eng Comput. 2019; 58(1):41-53. DOI: 10.1007/s11517-019-02066-y. View

Lao Y, Jia B, Yan P, Pan M, Hui X, Li J . Diagnostic accuracy of machine-learning-assisted detection for anterior cruciate ligament injury based on magnetic resonance imaging: Protocol for a systematic review and meta-analysis. Medicine (Baltimore). 2019; 98(50):e18324. PMC: 6922500. DOI: 10.1097/MD.0000000000018324. View

10.

Ahmadi Rastegar D, Ho N, Halliday G, Dzamko N . Parkinson's progression prediction using machine learning and serum cytokines. NPJ Parkinsons Dis. 2019; 5:14. PMC: 6658482. DOI: 10.1038/s41531-019-0086-4. View

11.

Cseko G, Tremaine W . The role of the institutional review board in the oversight of the ethical aspects of human studies research. Nutr Clin Pract. 2013; 28(2):177-81. DOI: 10.1177/0884533612474042. View

12.

Ngiam K, Khor I . Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 2019; 20(5):e262-e273. DOI: 10.1016/S1470-2045(19)30149-4. View

13.

Kaminski B, Jakubczyk M, Szufel P . A framework for sensitivity analysis of decision trees. Cent Eur J Oper Res. 2018; 26(1):135-159. PMC: 5767274. DOI: 10.1007/s10100-017-0479-6. View

14.

Mesko B, Hetenyi G, Gyorffy Z . Will artificial intelligence solve the human resource crisis in healthcare?. BMC Health Serv Res. 2018; 18(1):545. PMC: 6044098. DOI: 10.1186/s12913-018-3359-4. View

15.

Malone B, Simovski B, Moline C, Cheng J, Gheorghe M, Fontenelle H . Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs. Sci Rep. 2020; 10(1):22375. PMC: 7758335. DOI: 10.1038/s41598-020-78758-5. View

16.

Wang D, Li J, Zhang Y, Chen L, Huang T, Cai Y . Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms. Genes (Basel). 2018; 9(3). PMC: 5867876. DOI: 10.3390/genes9030155. View

17.

Cui Z, Gong G . The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features. Neuroimage. 2018; 178:622-637. DOI: 10.1016/j.neuroimage.2018.06.001. View

18.

Siddiqui M, Morales-Menendez R, Huang X, Hussain N . A review of epileptic seizure detection using machine learning classifiers. Brain Inform. 2020; 7(1):5. PMC: 7248143. DOI: 10.1186/s40708-020-00105-1. View

19.

Vakulskas C, Dever D, Rettig G, Turk R, Jacobi A, Collingwood M . A high-fidelity Cas9 mutant delivered as a ribonucleoprotein complex enables efficient gene editing in human hematopoietic stem and progenitor cells. Nat Med. 2018; 24(8):1216-1224. PMC: 6107069. DOI: 10.1038/s41591-018-0137-0. View

20.

Sharabiani A, Bress A, Douzali E, Darabi H . Revisiting Warfarin Dosing Using Machine Learning Techniques. Comput Math Methods Med. 2015; 2015:560108. PMC: 4471424. DOI: 10.1155/2015/560108. View