{"id":78400,"date":"2026-06-18T14:07:08","date_gmt":"2026-06-18T14:07:08","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/78400\/"},"modified":"2026-06-18T14:07:08","modified_gmt":"2026-06-18T14:07:08","slug":"ai-pathology-platform-expands-to-more-hospitals-for-cancer-diagnostics","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/78400\/","title":{"rendered":"AI Pathology Platform Expands to More Hospitals for Cancer Diagnostics"},"content":{"rendered":"

Slideflow Labs, an artificial intelligence (AI) pathology<\/a> company spun out of research conducted at the University of Chicago, is advancing the deployment of its cloud-based precision diagnostics platform across several institutions, including the University of Chicago.<\/p>\n

The platform, Slideflow Pro, is designed to analyze digitized pathology slides and support the development of AI-based biomarkers to assist in cancer care. Alexander T Pearson<\/a>, associate professor of medicine, has developed computer vision models to predict genomic alterations directly from histology slides of tumor biopsy samples. Research<\/a> published in Nature Cancer showed that a single deep learning algorithm can be trained to predict molecular alterations, gene expression signatures, and molecular subtypes from routine slides.<\/p>\n

\u201cOur goal is to develop and deploy patient-facing biomarkers using histology samples that can answer questions in medicine that we can\u2019t answer today,\u201d says Sid Ramesh, co-founder and chief scientific officer of Slideflow Labs, in a release. \u201cThe first phase is to develop models and methods that are clinically impactful and can exceed the performance of highly utilized legacy tests.\u201d<\/p>\n

Scalability and Clinical Applications<\/p>\n

The platform is built to be scalable and modular, allowing for integration into various hospital settings. It works with multiple hardware options, allowing slides to be scanned, uploaded to the cloud, and analyzed in near real time, according to a release from the company. This approach is intended to reduce barriers for institutions that lack large-scale digital pathology<\/a> infrastructure or machine-learning expertise.<\/p>\n

\u201cThe goal is democratization; AI should not be something only a few major companies or institutions can use,\u201d says Ramesh in a release. \u201cSlideflow is built so physicians, pathologists, technicians, and health systems can all benefit from advanced AI capabilities in a practical and reliable way.\u201d<\/p>\n

The current clinical focus of the company is a breast cancer application<\/a>. This tool is designed to predict molecular subtype and recurrence risk<\/a>, which helps clinicians make decisions regarding adjuvant chemotherapy.<\/p>\n

Commercialization Milestones<\/p>\n

Slideflow Labs was recently selected for the 2026 Northwestern Medicine and Techstars Healthcare Accelerator, a three-month mentorship program. The company also won first place at the 2026 Edward L Kaplan, \u201971, New Venture Challenge at the University of Chicago, receiving a $575,000 prize.<\/p>\n

Future milestones for the company include expanding deployment, validating performance across institutions, and advancing regulatory pathways for clinical use. The team is also developing quality-control methods to ensure AI outputs are appropriate for patient-facing use.<\/p>\n

\u201cWe are focused on making sure the platform performs safely and effectively in real-world clinical environments,\u201d says Pearson in a release. \u201cThat means validating each model, meeting regulatory requirements, and building the infrastructure needed to scale across more institutions and more diagnostic applications.\u201d<\/p>\n

ID 240779282<\/a> \u00a9 Roman Zaiets<\/a> | Dreamstime.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"Slideflow Labs, an artificial intelligence (AI) pathology company spun out of research conducted at the University of Chicago,…\n","protected":false},"author":2,"featured_media":78401,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,42823,25,7285,7163,42824,42825,668,2459,7287,42826,6238,42827,42828,42829,360,13830],"class_list":["post-78400","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-ai-pathology","tag-artificial-intelligence","tag-biomarkers","tag-cancer-diagnostics","tag-clinical-applications","tag-cloud-based-platform","tag-computer-vision","tag-deep-learning","tag-digital-pathology","tag-genomic-alterations","tag-healthcare-technology","tag-histology","tag-hospital-integration","tag-molecular-subtypes","tag-precision-medicine","tag-scalability"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/78400","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=78400"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/78400\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/78401"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=78400"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=78400"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=78400"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}