Introduction to Artificial Intelligence (AI) and Machine Learning (ML) in Pathology & Medicine: Generative & Non-Generative AI Basics

Hooman H Rashidi; Joshua Pantanowitz; Mathew 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

doi:10.1016/j.modpat.2024.100688

Introduction to Artificial Intelligence (AI) and Machine Learning (ML) in Pathology & Medicine: Generative & Non-Generative AI Basics

Mod Pathol. 2025 Jan 2:100688. doi: 10.1016/j.modpat.2024.100688. Online ahead of print.

Authors

Affiliations

¹ Department of Pathology, University of Pittsburgh Medical Center, PA, USA; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address: [email protected].
² School of Medicine, University of Pittsburgh, PA, USA.
³ Department of Pathology, University of Pittsburgh Medical Center, PA, USA; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁴ Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁵ Department of Medicine, UCSF, School of Medicine, San Francisco, CA.
⁶ Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH.
⁷ Division of Neuropathology, Department of Pathology, University of Pittsburgh School of Medicine and Medical Center; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁸ Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Mechanical Engineering, Istanbul Technical University, Istanbul, 34437, Turkey.
⁹ Department of Pathology, UC Davis, School of Medicine, Sacramento, CA.
¹⁰ Department of Pathology, University of Pittsburgh Medical Center, PA, USA; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address: [email protected].

PMID: 39755237
DOI: 10.1016/j.modpat.2024.100688

Abstract

This manuscript serves as an introduction to a comprehensive seven-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 non-generative (traditional) AI. Thereby serving as a primer to the other six 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 healthcare system.

Keywords: Artificial intelligence (AI); Chat-GPT; DALL-E; GAN (generative adversarial network); GPT (generative pretrained transformer); Generative AI; machine learning (ML); neural network; non-generative AI; predictive analytics; reinforcement learning; stable diffusion; supervised ML; unsupervised ML.

Publication types

Review