arXiv (All)
open access
Expert Opinion Elicitation for Assisting Deep Learning based Lyme Disease Classifier with Patient Data
Diagnosing erythema migrans (EM) skin lesion, the most common early symptom of Lyme disease using deep learning techniques can be effective to prevent long-term complications. Existing works on deep learning based EM recognition only utilizes lesion image due to the lack of a dataset of Lyme disease
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images#1247226
- IViT: A Novel Interpretable Visual Transformer for Skin Disease Detection#1052211
- Enhancing breast cancer detection accuracy through machine learning, deep learning and transfer learning techniques for clinical practice.#489469
- CAMEO: A Class-Activation-Mapped Equitable Overlay Framework for Fair and Robust Deep Learning-based Skin Condition Diagnosis#1131242
- Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician#686443
Record · ID 1247228
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive