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Artificial Intelligence (AI) in Pathology

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The College of American Pathologists (CAP) is working to stay abreast of artificial intelligence (AI) advancements in pathology. Here we explore the transformative role of AI within our specialty, offering valuable insights, educational materials, and practical guidance for pathologists at all levels. As AI technology continues to evolve, our commitment to advancing pathology practices through innovative tools and techniques remains at the forefront. Dive in to discover how AI can enhance diagnostic accuracy, streamline workflows, and ultimately improve patient care.

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Recent News

  • PathAI Launches Precision Pathology Network to Advance AI-Powered Pathology | The National Law Review
    PathAI has launched the Precision Pathology Network (PPN), a digital pathology network connecting laboratories through its AISight Image Management System. PPN members get early access to AI-powered tools co-developed with biopharma partners; they also gain new revenue opportunities through real-world data sharing, and can participate in evidence generation and clinical trial initiatives. The network hopes to bring together industry, academia, and clinical labs to advance precision diagnostics and accelerate AI adoption.
  • Proscia Raises $50M to Advance AI-Driven Pathology and Deliver the Future of Precision Medicine | Markets Insider
    Proscia has secured $50 million in new funding (bringing its total to $130 million) to expand its Concentriq platform, which now supports diagnoses for over 22,000 patients every day and is used by 16 of the top 20 pharmaceutical companies. The company is using AI to accelerate diagnostics, support drug development, and connect labs and life sciences organizations in a precision medicine ecosystem. With this investment, Proscia aims to deepen AI integration, scale adoption through OEM partnerships, and advance novel biomarker and therapeutic discovery.
  • A Healthcare System in LA Is Using AI to Provide 24/7 Patient Care | Business Insider 
    In order to address limited access, lengthy wait times, and administrative task burden on physicians, Cedars-Sinai (in conjunction with K Health) has launched CS Connect, a 24/7 AI-powered virtual healthcare platform that performs patient intake, triage, information summary, and management recommendations for physician review. Clinical indication is often important for interpretation of biopsies and other pathological studies, and such indications may be influenced pre-analytically by the suggestion of AI. In the future, similar models could be made available to pathologists to summarize clinical, imaging, and other patient information from the electronic health record to guide and make recommendations for biopsy interpretation.
  • Meta Yann LeCun Says AI Needs These 2 Key Guardrails | Business Insider 
    Yann LeCun, Meta's Chief AI Scientist, argues that safe AI requires two fundamental design principles: unwavering submission to human direction and a built-in sense of empathy. He compares these principles to human instincts, advocating for "objective-driven AI" that operates strictly within boundaries defined by people, reflecting growing concerns around safety, deception, and ethical oversight in AI systems.

Note: References to vendors, products, or services in this section are for informational purposes only. The College of American Pathologists does not endorse, recommend, or guarantee any vendor or offering mentioned.

CAP Advocacy Updates

Definitions of Artificial Intelligence and Machine Learning

Artificial intelligence (AI) is a broad field concerning the development of machines that mimic human capabilities. In recent years, AI has progressed from performing narrow tasks—like outperforming humans in board games—to generalizing across problem domains in science, mathematics, and the creative arts. 

The most common method of developing AI is machine learning (ML), which uses software algorithms to recognize new patterns in data. Typically, this involves training a model on significant amounts of input data—text, images, even video—and predicting a task-specific output. In pathology, large-scale AI models called "foundation models" are trained on millions of histology images and text reports to produce increasingly accurate diagnostic and prognostic systems.

  1. Lu MY, Chen B, Williamson DFK, et al. A multimodal generative AI copilot for human pathology. Nature. 2024;634(8033):466-473. doi: 10.1038/s41586-024-07618-3. Epub 2024 Jun 12. PMID: 38866050; PMCID: PMC11464372. 

AI in Pathology Deep Dive

A collection of multi-part series designed to build a foundational understanding of artificial intelligence (AI) in pathology today while exploring the possibilities for its future.

7-Part Artificial Intelligence Review Series: A Guided Journey Into the Future of Pathology and Medicine

The seven-part review series by Hooman H. Rashidi, MD, MS, FCAP; Matthew G. Hanna, MD, FCAP; and Liron Pantanowitz, MD, PhD, FCAP, provides a comprehensive, structured introduction to AI and machine learning (ML) in medicine and pathology. It begins with foundational concepts and terminology, then explores both generative (eg, large language models, image synthesis) and non-generative (eg, predictive analytics) AI applications. The series also covers model evaluation and performance metrics, regulatory frameworks (including FDA pathways), and ethical considerations such as bias and privacy, then concludes with practical guidance on operationalizing AI in clinical environments (MLOps). Aimed at clinicians, researchers, and innovators, the series offers accessible, high-level insight into how AI can be responsibly integrated into biomedical and pathology practices.

The series includes: 

Integrating Generative AI Into Pathology and Laboratory Medicine: 5-Part Series

Generative AI will have a great influence on the future of clinical and anatomic pathology, as well as pathology education. The CAP, the Association for Pathology Informatics (API), and the Digital Pathology Association (DPA) have launched a new Archives of Pathology & Laboratory Medicine topic series exploring the benefits and challenges of this technology.

The series includes:

Podcasts

  • How Pathologists Can Leverage AI to Improve Patient Care 
    Artificial intelligence is streamlining processes within health care, particularly related to diagnosing and managing patient care. In this interview with Becker's Healthcare, M.E. (Doc) de Baca, MD, FCAP, chair of the College of American Pathologists’ Council on Informatics and Pathology Innovation, discusses the complexities of integrating AI into patient care, considering the practical, ethical and collaborative aspects that need to be addressed for effective implementation and improved health outcomes.
  • AI and Readiness—Present and Future Implications for AI Growth on the Field of Pathology 
    Peter McCaffrey, MD, FCAP, and M. E. de Baca, MD, FCAP, discuss the "AI and Readiness" course they led at the 2023 Pathologists Leadership Summit. They share some of the potential benefits, limitations, and implications of AI's growth in pathology testing.
  • Artificial Intelligence in Precision Medicine 
    Artificial intelligence is an exciting technology that is directly affecting the practice of pathology. When AI is applied to the area of precision medicine, especially to treat oncologic disease, it opens even more frontiers for providing better patient care. This episode, a joint effort between the Personalized Health Care and Digital and Computational Pathology Committees, features Marilyn M. Bui, MD, PhD, FCAP, and Eric E. Walk, MD, FCAP, discussing machine learning developments and the future of AI in precision medicine.
  • Digital Pathology Implementation at UoL Health 
    S. Joseph Sirintrapun, MD, FCAP, and Dibson D. Gondim, MD, FCAP, discuss implementing digital pathology at UofL Health. Dr. Gondim shares the challenges and easy wins that the University of Louisville experienced during the process and how artificial intelligence will continue to impact digital pathology in the next five to 10 years. 

Webinars

  • Artificial Intelligence 101: AI Essentials for Pathology Laboratories
    Presenter: Hooman H. Rashidi, MD, MS, FCAP 
    This introductory webinar offers pathologists and laboratory professionals a foundational understanding of artificial intelligence (AI) and its relevance to clinical practice. Participants will explore key AI concepts—such as generative vs. non-generative AI—and learn how AI is being used to enhance diagnostic accuracy, efficiency, and patient outcomes in pathology.
  • AI 201: Synthetic Data & Generative AI 
    Presenter: Hooman H. Rashidi, MD, MS, FCAP 
    Building on the concepts from AI 101 (see above), this next webinar delves into more advanced AI applications, including synthetic data generation and auto-machine learning tools. Participants will explore how these technologies bridge the gap between generative and non-generative AI, enhancing diagnostic accuracy, workflow efficiency, and personalized care.
  • Exploring Image-to-Image Search Using Foundational Models and Vector Databases
    Presenter: Dibson Dibe Gondim, MD, FCAP 
    This webinar explores how image-to-image search technology can transform the diagnosis of rare cases by enabling non-specialist pathologists to approach diagnoses with greater assurance. Attendees will learn the core principles behind this AI-driven approach and review real-world examples of its implementation in clinical practice.
  • Practical Applications of Artificial Intelligence in Clinical Microbiology 
    Presenter: Daniel D. Rhoads, MD, D(ABMM), FCAP 
    This webinar is designed for microbiology laboratories looking to harness the power of AI and machine learning to manage growing volumes of complex data. Attendees will learn foundational AI concepts and explore practical examples of how machine learning can enhance both efficiency and quality in clinical microbiology. 

The CAP Council on Informatics and Pathology Innovation (CIPI)

  • Identifies and recommends strategic direction on current and emerging medical information science, data science, and computational technologies that could affect the practice of pathology
  • Provides the CAP with informatics domain information and expertise in furtherance of its programs and mission
  • Guides efforts to help pathologists stay up to date and plan for future innovations
  • Supports appropriate engagement with external stakeholders

The AI Committee, Cancer Committee, Digital and Computational Pathology Committee, Informatics Committee, and Pathology Electronic Reporting Committee (PERT) are members of CIPI. Through service on these committees, members contribute their domain expertise to help the CAP lead the way into the future of pathology.

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