AI in Histopathology Explorer for comprehensive analysis of the evolving AI landscape in histopathology: AI in histopathology explorer for facilitating assessment and translation of AI applications.

TY - JOUR

T1 - AI in Histopathology Explorer for comprehensive analysis of the evolving AI landscape in histopathology

T2 - AI in histopathology explorer for facilitating assessment and translation of AI applications.

AU - Ma, Yingrui

AU - Jamdade, Shivprasad

AU - Konduri, Lakshmi

AU - Sailem, Heba

N1 - Publisher Copyright: © The Author(s) 2025.

PY - 2025/3/12

Y1 - 2025/3/12

N2 - Digital pathology and artificial intelligence (AI) hold immense transformative potential to revolutionize cancer diagnostics, treatment outcomes, and biomarker discovery. Gaining a deeper understanding of deep learning algorithm methods applied to histopathological data and evaluating their performance on different tasks is crucial for developing the next generation of AI technologies. To this end, we developed AI in Histopathology Explorer (HistoPathExplorer); an interactive dashboard with intelligent tools available at www.histopathexpo.ai. This real-time online resource enables users, including researchers, decision-makers, and various stakeholders, to assess the current landscape of AI applications for specific clinical tasks, analyze their performance, and explore the factors influencing their translation into practice. Moreover, a quality index was defined for evaluating the comprehensiveness of methodological details in published AI methods. HistoPathExplorer highlights opportunities and challenges for AI in histopathology, and offers a valuable resource for creating more effective methods and shaping strategies and guidelines for translating digital pathology applications into clinical practice.

AB - Digital pathology and artificial intelligence (AI) hold immense transformative potential to revolutionize cancer diagnostics, treatment outcomes, and biomarker discovery. Gaining a deeper understanding of deep learning algorithm methods applied to histopathological data and evaluating their performance on different tasks is crucial for developing the next generation of AI technologies. To this end, we developed AI in Histopathology Explorer (HistoPathExplorer); an interactive dashboard with intelligent tools available at www.histopathexpo.ai. This real-time online resource enables users, including researchers, decision-makers, and various stakeholders, to assess the current landscape of AI applications for specific clinical tasks, analyze their performance, and explore the factors influencing their translation into practice. Moreover, a quality index was defined for evaluating the comprehensiveness of methodological details in published AI methods. HistoPathExplorer highlights opportunities and challenges for AI in histopathology, and offers a valuable resource for creating more effective methods and shaping strategies and guidelines for translating digital pathology applications into clinical practice.

KW - Artificial Inteelgence

KW - Digital pathology

KW - Deep learning

KW - histopathology

KW - Diagnosis, Computer-Assisted

KW - Prognostic biomarker

KW - biomarker

KW - foundation model

UR - http://www.scopus.com/inward/record.url?scp=105000048226&partnerID=8YFLogxK

U2 - 10.1038/s41746-025-01524-2

DO - 10.1038/s41746-025-01524-2

M3 - Article

SN - 2398-6352

VL - 8

JO - npj Digital Medicine

JF - npj Digital Medicine

IS - 1

M1 - 156

ER -