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Introduction to Artificial Intelligence and Machine Learning in Pathology and Medicine: Generative and Nongenerative Artificial Intelligence Basics

  • Hooman H. Rashidi*
  • , Joshua Pantanowitz
  • , Matthew G. Hanna
  • , Ahmad P. Tafti
  • , Parth Sanghani
  • , Adam Buchinsky
  • , Brandon Fennell
  • , Mustafa Deebajah
  • , Sarah Wheeler
  • , Thomas Pearce
  • , Ibrahim Abukhiran
  • , Scott Robertson
  • , Octavia Palmer
  • , Mert Gur
  • , Nam K. Tran
  • , Liron Pantanowitz
  • *Bu çalışma için yazışmadan sorumlu yazar
  • University of Pittsburgh
  • University of California at San Francisco
  • Cleveland Clinic Foundation
  • University of California at Davis

Araştırma çıktısı: Dergi yayınıİnceleme makalesiHakemli

66 Atıf (Scopus)

Özet

This manuscript serves as an introduction to a comprehensive 7-part review article series on artificial intelligence (AI) and machine learning (ML) and their current and future influence within pathology and medicine. This introductory review provides a comprehensive grasp of this fast-expanding realm and its potential to transform medical diagnosis, workflow, research, and education. Fundamental terminology employed in AI-ML is covered using an extensive dictionary. The article also provides a broad overview of the main domains in the AI-ML field, encompassing both generative and nongenerative (traditional) AI, thereby serving as a primer to the other 6 review articles in this series that describe the details about statistics, regulations, bias, ethical dilemmas, and ML-Ops in AI-ML. The intent of these review articles is to better equip individuals who are or will be working in an AI-enabled health care system.

Orijinal dilİngilizce
Makale numarası100688
DergiModern Pathology
Hacim38
Basın numarası4
DOI'lar
Yayın durumuYayınlandı - Nis 2025

Bibliyografik not

Publisher Copyright:
© 2024 The Authors

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