Mahmood Lab
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About
Mahmood Lab focuses on developing machine learning, data fusion, and medical image analysis methods for objective diagnosis, prognosis, and biomarker discovery. It aims to develop automated and objective mechanisms for reducing interobserver and intraobserver variability in cancer diagnosis using artificial intelligence as an assistive tool for pathologists. The lab also focuses on the development of new algorithms and methods to identify clinically relevant morphologic phenotypes and biomarkers associated with response to specific therapeutic agents. They develop multimodal fusion algorithms for combining information from multiple imaging modalities, familial and patient histories and multi-omics data to make more precise diagnostic, prognostic and therapeutic determinations.
Platform
Task
Features
• data fusion
• large scale batch processing of pathology wsis and foundation model benchmarking
• ai-driven 3d spatial transcriptomics
• multimodal fusion algorithms for combining information from multiple imaging modalities, familial and patient histories and multi-omics data
• identification of clinically relevant morphologic phenotypes and biomarkers
• automated mechanisms for reducing interobserver and intraobserver variability in cancer diagnosis
• medical image analysis methods
• machine learning for objective diagnosis
Pricing Plans
Academic Use
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