Rajesh Chandra Dash

Future of Artificial Intelligence—Machine Learning Trends in Pathology and Medicine

Modern Pathology · 2025-01-04 · 136 citations

Recommendations for Performance Evaluation of Machine Learning in Pathology: A Concept Paper From the College of American Pathologists

Archives of Pathology & Laboratory Medicine · 2023-12-02 · 32 citations

CONTEXT.—: Machine learning applications in the pathology clinical domain are emerging rapidly. As decision support systems continue to mature, laboratories will increasingly need guidance to evaluate their performance in clinical practice. Currently there are no formal guidelines to assist pathology laboratories in verification and/or validation of such systems. These recommendations are being proposed for the evaluation of machine learning systems in the clinical practice of pathology. OBJECTI…

Introduction to Generative Artificial Intelligence: Contextualizing the Future

Archives of Pathology & Laboratory Medicine · 2024-12-04 · 10 citations

CONTEXT.—: Generative artificial intelligence (GAI) is a promising new technology with the potential to transform communication and workflows in health care and pathology. Although new technologies offer advantages, they also come with risks that users, particularly early adopters, must recognize. Given the fast pace of GAI developments, pathologists may find it challenging to stay current with the terminology, technical underpinnings, and latest advancements. Building this knowledge base will e…

Advancements in Interoperability: Achieving Anatomic Pathology Reports That Adhere to International Standards and Are Both Human-Readable and Readily Computable

JCO Clinical Cancer Informatics · 2025-02-01 · 4 citations

PURPOSE: Over the past 50 years, multiple pathology organizations worldwide have evolved in cancer histopathology reporting from subjective, narrative assessments to structured, synoptic formats using controlled vocabulary. These reporting protocols include the required data elements that represent the minimum set of evidence-based, clinically actionable parameters necessary to convey the diagnostic, prognostic, and predictive information essential for patient care. Despite these advances, the s…

The critical role of standards for AI in digital pathology

Journal of Pathology Informatics · 2026-02-04 · 3 citations

Background: The field of pathology has not yet fully realized the potential of artificial intelligence (AI) and digital pathology. Adoption must be driven by demonstrable utility, and successful implementation depends on interoperability and sustainability, which require established standards. We address the imminent challenges facing the field of AI in digital pathology, which currently suffers from a lack of coordinated and adopted standards. Methods: We conducted several roundtable discussion…