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pathology

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People, technologies and companies concerned with pathology and its digitisation. 19 records carry it: 12 technologies, 5 people, 1 front, 1 company.

19 records
Anna Sapino
Scientific Director · Istituto di Candiolo IRCCS (FPO)
Pathologist and Scientific Director of the Candiolo Cancer Institute (INOC), Piedmont's oncology IRCCS and an OECI-certified Comprehensive Cancer Centre.
Atlas (Aignostics, Mayo Clinic, Charité)
Atlas is a pathology foundation model trained on 1.2 million slides from two of the world's largest hospitals.
CHIEF (Harvard, Yu Lab)
A pathology model trained across 19 cancer types that predicts survival and mutations from slides.
Diagnostics & Biomarkers
Tests on tissue and blood that say what kind of cancer it is, what is driving it, and which drugs might work.
Faisal Mahmood
Associate Professor of Pathology, Harvard Medical School and Brigham and Women's Hospital; Associate Member, Broad Institute · Broad Institute of MIT and Harvard
Built UNI and CONCH, the pathology foundation models that let AI read whole-slide images across cancer types.
H-optimus (Bioptimus)
An open 1.1-billion-parameter pathology model from a French startup, among the strongest on public benchmarks.
Hibou (HistAI)
Hibou is a family of open pathology foundation models under a permissive licence.
Jakob Nikolas Kather
Professor of Clinical Artificial Intelligence, Else Kröner Fresenius Center for Digital Health, TU Dresden; Medical Oncologist, NCT Dresden · NCT/UCC Dresden, University Hospital Carl Gustav Carus
Showed that deep learning can read genetic features like microsatellite instability directly from routine pathology slides.
Midnight (kaiko.ai)
Midnight is a pathology model that matched the leaders while training on far fewer slides.
MUSK (Stanford, vision-language pathology)
A model that reads slides and clinical text together to predict who will respond to immunotherapy.
Phikon / Phikon-v2 (Owkin)
Owkin's open pathology models trained on TCGA and its federated hospital network.
PLUTO (PathAI)
PLUTO is PathAI's compact pathology foundation model, a vision transformer pretrained at several magnifications on 195 million tiles from 158,000 slides, so one network serves slide-level and biomarker quantification tasks at whatever resolution each needs. It runs inside PathAI's AISight product, but its weights are proprietary, so outside groups cannot benchmark or adapt it.
Prov-GigaPath (Microsoft, Providence)
An open pathology model trained on 1.3 billion image tiles from a US health system, modelling whole slides at gigapixel scale.
Strand AI
San Francisco, CA, US · YC W26
Strand AI's first model, Lattice, predicts which proteins sit where across a tumour from the ordinary stained slide a hospital already has, so a whole archive can be profiled without spending tissue on extra laboratory staining.
Sunil Lakhani
Chair of the Board · Breast Cancer Trials
Brisbane breast pathologist who chairs the board of Breast Cancer Trials, the Australia and New Zealand breast cancer clinical trials group.
Thomas J. Fuchs
Dean of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai; Co-founder, Paige · The Mount Sinai Hospital / Tisch Cancer Institute
Trained the first clinical-grade AI on tens of thousands of slides, leading to the first FDA-authorised AI pathology product.
TITAN (whole-slide multimodal model)
TITAN is a model that summarises a whole slide, not just tiles, and can write a draft pathology report.
UNI and CONCH (Harvard, Mahmood Lab)
Two open academic pathology models: UNI reads tissue images, CONCH links images with pathology text.
Virchow / Virchow2 (Paige, MSK)
A pathology foundation model trained on millions of slides that can detect cancer and predict biomarkers from an ordinary H&E slide.

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