Artificial intelligence in primary care

Adham El Sherbini, Benjamin S. Glicksberg, Chayakrit Krittanawong

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

An overview of the promise, restrictions, and difficulties of artificial intelligence (AI) in revolutionizing primary care is given in this chapter. The application of AI, machine learning, and deep learning in healthcare has made significant strides in several primary care domains, including screening, preoperative care, and disease diagnosis. Numerous diseases, including cancer, cardiovascular disease, sexually transmitted diseases, osteoporosis, diabetes mellitus, hypertension, ophthalmic diseases, and obstructive sleep apnea, have been successfully predicted, diagnosed, and risk assessed using AI models. For the widespread adoption of AI in primary care, issues including data quality, interpretability, and regulatory constraints must be resolved. Nevertheless, by enhancing disease diagnosis, risk assessment, and personalized care, AI has the potential to transform primary care.

Original languageEnglish
Title of host publicationArtificial Intelligence in Clinical Practice
Subtitle of host publicationHow AI Technologies Impact Medical Research and Clinics
PublisherElsevier
Pages1-13
Number of pages13
ISBN (Electronic)9780443156885
ISBN (Print)9780443156892
DOIs
StatePublished - 1 Jan 2023

Keywords

  • Artificial intelligence
  • machine learning
  • preoperative care
  • primary care
  • risk assessment
  • screening

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