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SPIDER Skin Model

Developed by histai
The SPIDER-Skin Model is a deep learning model specifically designed for skin pathology slide classification, part of the SPIDER Dataset Initiative.
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Release Time : 3/4/2025

Model Overview

This model is used for skin pathology slide classification tasks, trained on a large-scale, high-quality, multi-organ pathology dataset with expert-annotated labels.

Model Features

High-Quality Dataset Support
Trained on the SPIDER-Skin Dataset, which includes 159,854 center slides and 2,696,987 total slides, covering 24 skin pathology categories.
High-Accuracy Classification
Achieves an accuracy of 0.940, precision of 0.936, and F1 score of 0.938 in skin pathology slide classification tasks.
Professional Medical Application
Designed specifically for medical pathology analysis, supporting the identification and classification of various skin lesions.

Model Capabilities

Skin Pathology Slide Classification
Medical Image Analysis
Multi-Category Recognition

Use Cases

Medical Diagnosis
Skin Lesion Identification
Automatically identifies and classifies various lesion types in skin pathology slides, such as basal cell carcinoma and melanoma.
Can assist pathologists in improving diagnostic efficiency and accuracy.
Medical Research
Used for large-scale research and data analysis in skin pathology.
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