Article

Histological triage of early-stage mycosis fungoides using a weakly supervised deep learning-based model: a multicentre, external validation, and clinical utility study

2026-07-28

Abstract excerpt

<h4>Summary</h4> <h4>Background</h4> Histological diagnosis of early-stage mycosis fungoides (MF) is hindered by profound overlap with benign inflammatory dermatoses (BIDs), leading to diagnostic delays and extensive ancillary testing. We developed MIMIC (Multiple Instance-learning for Identification of Mycosis fungoides In Cutaneous biopsies), a weakly supervised deep learning model designed as a triage tool at...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 853d151a-f167-5fa4-a44b-5672c116de66
DOI: 10.64898/2026.07.27.26359009

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Histological triage of early-stage mycosis fungoides using a weakly supervised deep learning-based model: a multicentre, external validation, and clinical utility studyDOI 10.64898/2026.07.27.26359009Read

Robust and accurate diagnosis of infectious skin diseases from histopathology images by integrating deep learning and explainable AISemantic proximity Read

Case-level artificial intelligence for multi-photo teledermatology submissions: development and internal validation using patient-submitted dermatology imagesSemantic proximity Read

Predicting the Clinical Management of Skin Lesions using Deep LearningSemantic proximity Read

Search and Retrieval in Dermatology Atlases of Histopathology Images for Risk Stratification of Cutaneous Squamous Cell CarcinomaSemantic proximity Read

XpressO-Melanoma: An Explainable Deep Learning Model for the Prediction of BRAF V600 Mutation Status in Cutaneous MelanomasSemantic proximity Read

Multimodal Machine Learning Approach for Diagnosing Atopic DermatitisSemantic proximity Read

Multimodal Image Dataset for AI-based Skin Cancer (MIDAS) BenchmarkingSemantic proximity Read

Use of artificial intelligence as a diagnostic support tool for skin lesions in primary care: feasibility study in clinical practiceSemantic proximity Read

SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic ImagesSemantic proximity Read

Dual-stage AI system for Pathologist-Free Tumor Detection and subtyping in Oral Squamous Cell CarcinomaSemantic proximity Read

LCK and HOMER1 gene expression-based classifier distinguishes early mycosis fungoides from eczema and psoriasisSemantic proximity Read