Advancing AI-Driven Pathology Research
- About SmartPath
- Our Mission
- Collecting and curating high-quality pathology images, de-identified pathology reports, molecular data, and patient treatment responses.
- Developing AI-driven methodologies to analyze pathology data with unprecedented accuracy and scale.
- Fostering collaborations between academic institutions, hospitals, and AI research centers globally.
- Ensuring ethical and secure data-sharing frameworks that adhere to the highest standards of patient privacy and confidentiality.
- Our Approach
- A Pathology AI Foundation Model for Cancer Diagnosis and Prognostic Prediction (Nature, 2024): This study presents a foundational AI model trained on diverse pathology images, enhancing diagnostic accuracy and prognostic predictions across various cancer types.
- AI for Real-Time Brain Cancer Diagnosis during Surgery (Med, 2023): This project established an AI framework to analyze frozen section pathology samples obtained during surgery, enabling rapid and accurate classification of brain cancers in accordance with the latest WHO guidelines.
- Multi-Omics Profile Predicting using Pathology Images (Nature Communications, 2023): This work demonstrates how AI can analyze histopathology images to predict genetic mutations and patient outcomes, facilitating personalized treatment strategies for colorectal cancer.
- Collaboration & Data Sharing
- Join SmartPath
SmartPath is a pathology artificial intelligence (AI) research network dedicated to revolutionizing cancer diagnostics and the study of complex diseases. Our initiative brings together a global network of researchers, pathologists, and data scientists to harness the power of artificial intelligence in pathology. By integrating multimodal data, SmartPath aims to drive innovations in precision medicine, improve diagnostic accuracy, and enhance personalized treatment strategies for patients worldwide.
SmartPath is committed to:
The SmartPath research network develops state-of-the-art deep learning models and computational pathology techniques to extract meaningful insights from complex datasets. By integrating molecular profiling with digital pathology, we aim to uncover novel biomarkers, predict treatment responses, and support precision medicine in oncology and the management of other complex diseases. Recent papers from our research network include:
We welcome collaborations with researchers, healthcare institutions, and industry partners to expand our knowledge base and refine AI-powered pathology tools. Our data-sharing infrastructure ensures compliance with regulatory standards while enabling impactful discoveries that drive clinical advancements.
Are you interested in collaborating with us or contributing to our research network? Contact us (Kun-Hsing_Yu AT hms DOT harvard DOT edu) to learn more about partnership opportunities, data access, and ongoing projects at SmartPath.
For more information, visit Yu Lab at Harvard Medical School.