Balaji V, Suganthi S, Rajadevi R, Kumar VK, Balaji BS, Pandiyan S (2020) Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes classifier. Measurement 163:107922 Article Google Scholar Baskar R, Lee KA, Yeo R, Yeoh K-W (2012) Can...
Here, a Random Forest-based machine learning model is used to detect lumpy skin disease. The data used for training and validation of lumpy skin disease available on Kaggle is used. The proposed model has shown an accuracy of 98%.Patel, Shrey...
Rest of the paper is organized as follows: In “Related work” section the literature study related to skin cancer detection is explored using different techniques. The materials used for proposing the model is explain in “Materials and methods” section evaluate result based on different terms is...
The successful classification of monkeypox skin lesions can aid in the early detection, diagnosis, and treatment of the disease, ultimately resulting in improved patient outcomes. Objectives The objectives of this study are to propose a novel approach for classifying monkeypox skin lesions using CNNs...
Previous studies have developed systems based on the diagnosis of this disease with the help of deep learning (DL), which can detect cancer in its early stages. In this study, using the Kaggle Melanoma Skin Cancer Dataset of 10000 Images dataset, which consists of over 10,000 ...
A Transfer Learning Approach for Clinical Detection Support of Monkeypox Skin Lesionsdoi:10.3390/diagnostics13081503MONKEYPOXMEDICAL personnelCOMMUNICABLE diseasesSKIN imagingDEEP learningCARRIER state (Communicable diseases)Monkeypox (MPX) is a disease caused by monkeypox virus (MP...
A Multi-Stage Faster RCNN-Based iSPLInception for Skin Disease Classification Using Novel Optimization Article 15 June 2023 Melanoma skin cancer detection based on deep learning methods and binary Harris Hawk optimization Article Open access 02 September 2024 Explore related subjects Discover the ...
3) which demonstrates the early detection ability of the MPXV-CNN. Also, MPXV skin lesions with a duration of the presence of 7 d or more were detected reliably (TPR = 84.6%) illustrating the ability of the MPXV-CNN to recognize skin lesions in different disease stages. The ...
We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors’ notes, and designing a two-step training ...
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