Brendan O'Fallon, Lauren Zuromski, Paul English, Muir Morrison, Alexandra Rangel, David Ng, Nicholas Spies
{"title":"A general purpose hematopathology foundation model trained on over 27,000 whole slide images","authors":"Brendan O'Fallon, Lauren Zuromski, Paul English, Muir Morrison, Alexandra Rangel, David Ng, Nicholas Spies","doi":"10.1016/j.jpi.2026.100559","DOIUrl":"10.1016/j.jpi.2026.100559","url":null,"abstract":"","PeriodicalId":37769,"journal":{"name":"Journal of Pathology Informatics","volume":"21 ","pages":"Article 100559"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148177789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Rivera, Alex Banerjee, Jacob Huddin, Rongzhen Zhang, Brenda Mai, Hanadi El Achi, Jacob Armstrong, Amer Wahed, Nghia Nguyen
{"title":"Vision transformer model for diagnosis of lymphomas: A comparison to convolutional neural network","authors":"Daniel Rivera, Alex Banerjee, Jacob Huddin, Rongzhen Zhang, Brenda Mai, Hanadi El Achi, Jacob Armstrong, Amer Wahed, Nghia Nguyen","doi":"10.1016/j.jpi.2026.100565","DOIUrl":"10.1016/j.jpi.2026.100565","url":null,"abstract":"","PeriodicalId":37769,"journal":{"name":"Journal of Pathology Informatics","volume":"21 ","pages":"Article 100565"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148183655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Perceptions of digital pathology among healthcare workers in pathology","authors":"Aditi Tayal, Meghan E. Kapp, Sylvia L. Asa","doi":"10.1016/j.jpi.2026.100652","DOIUrl":"10.1016/j.jpi.2026.100652","url":null,"abstract":"<div><div>The integration of informatics into pathology is rapidly transforming the field, with the potential to enhance diagnostic accuracy, streamline workflows, and improve patient outcomes. Digital pathology, artificial intelligence (AI), and machine learning are among the innovations revolutionizing traditional practices by enabling the digitization of tissue samples, the automation of data analysis, and the incorporation of large datasets into diagnostic processes. While these advancements hold great promise, they have also generated mixed reactions among healthcare professionals, particularly in pathology, where the balance between human expertise and technology is critical. To better understand the perceptions of informatics in pathology, a cross-sectional survey was conducted among healthcare workers within the field. The survey aimed to assess attitudes toward the adoption of informatics, with specific focus on its perceived benefits and challenges. This study seeks to provide insights into how these new technologies are being received by those at the forefront of pathology, exploring both the enthusiasm and apprehension surrounding the growing role of informatics in the discipline.</div></div>","PeriodicalId":37769,"journal":{"name":"Journal of Pathology Informatics","volume":"21 ","pages":"Article 100652"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jun Fukuoka , Frederico Gaia Costa da Silva , Kris Lami , Wataru Uegami
{"title":"Human and AI collaboration to embrace diagnostic diversity and redefine ground truth","authors":"Jun Fukuoka , Frederico Gaia Costa da Silva , Kris Lami , Wataru Uegami","doi":"10.1016/j.jpi.2026.100556","DOIUrl":"10.1016/j.jpi.2026.100556","url":null,"abstract":"","PeriodicalId":37769,"journal":{"name":"Journal of Pathology Informatics","volume":"21 ","pages":"Article 100556"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148177790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}