Skill UI

PathML is a Python toolkit for computational pathology workflows, loading 160+ slide formats, preprocessing H&E images, constructing spatial graphs, training HoVer-Net/HACTNet models, and analyzing multiplex imaging for ML-ready pathology data.

This skill provides comprehensive support for generating high-stakes clinical documentation, including case reports (CARE guidelines), diagnostic summaries (radiology/pathology), clinical trial reports (ICH-E3), and patient progress notes (SOAP/H&P). It mandates adherence to strict regulatory standards (HIPAA, FDA, ICH-GCP) and integrates AI-generated scientific schematics to ensure the final output is accurate, compliant, and publication-ready.

Histolab is a specialized Python library for digital pathology research, enabling robust processing of Whole Slide Images (WSI). It automates complex workflows including tissue detection, sophisticated segmentation, and flexible tile extraction from various formats (SVS, TIFF). This tool is crucial for preparing structured, high-quality datasets required for deep learning models and advanced computational pathology analysis.

PathML is a comprehensive Python framework designed for computational pathology workflows. It supports end-to-end analysis of Whole Slide Images (WSI), including loading 160+ proprietary formats, performing advanced stain normalization and tissue segmentation, constructing spatial cell graphs, and training deep learning models (e.g., HoVer-Net) for multiplex immunofluorescence and spatial proteomics. Ideal for large-scale biomedical image analysis.

This structured tutor is designed for medical and health sciences students, covering core areas like anatomy, physiology, pharmacology, and pathology. It moves beyond rote memorization by focusing on case-based learning, systems integration, and understanding underlying mechanisms. By practicing clinical reasoning and differential diagnosis, users can bridge the gap between basic science knowledge and complex clinical application, preparing them for major medical licensing exams.

Utilize the idc-index Python package to access and query massive public datasets from the NCI Imaging Data Commons (IDC). This skill allows users to search, download, and visualize large-scale radiology (CT, MR, PET) and pathology (slide) images. It is essential for AI model training, medical research, and complex medical data analysis.