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ENTITY Whole slide images for primary diagnostics in dermatopathology: a feasibility study.

Whole slide images for primary diagnostics in dermatopathology: a feasibility study.

PulseAugur coverage of Whole slide images for primary diagnostics in dermatopathology: a feasibility study. — every cluster mentioning Whole slide images for primary diagnostics in dermatopathology: a feasibility study. across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_223395 ·

    New pipeline streamlines WSI embedding extraction for computational pathology

    Researchers have developed a new pipeline for extracting embeddings from large whole-slide images (WSIs) used in computational pathology. This system decouples the process into three stages: patch generation, embedding …

  2. TOOL · CL_167803 ·

    PathSelect framework enables efficient WSI processing for vision-language models

    Researchers have developed PathSelect, a novel framework for efficiently processing gigapixel Whole-Slide Images (WSIs) with vision-language models. This method reformulates token pruning as a sequential selection proce…

  3. RESEARCH · CL_154310 ·

    AI models learn from pathologist attention for efficient histopathology analysis

    Researchers have developed two novel approaches for analyzing histopathological images, aiming to improve efficiency and accuracy in medical diagnostics. The first method, SASHA, utilizes deep reinforcement learning and…

  4. RESEARCH · CL_99696 ·

    New AI framework improves cancer prognosis analysis using semantic anchors

    Researchers have developed a new framework called Semantic-Anchored Evidential Fusion Survival (SAEFS) to improve the accuracy and reliability of whole-slide image analysis for cancer prognosis. SAEFS leverages Visual Q…

  5. RESEARCH · CL_70564 ·

    Gastric cancer AI model GRACE boosts pathologist accuracy

    Researchers have developed GRACE, a specialized foundation model for gastric cancer pathology, trained on a large dataset of over 48,000 whole-slide images. This model demonstrated superior performance compared to gener…

  6. RESEARCH · CL_15508 ·

    AI priors boost colorectal cancer MSI prediction across sites

    Researchers have developed a method to improve the generalization of foundation models for predicting microsatellite instability (MSI) status in colorectal cancer from whole slide images. By incorporating biologically m…