Recently, computer vision (CV) based disease diagnosis models have been utilized in various areas of healthcare. At the same time, deep learning (DL) and machine (ML) play a vital role healthcare sector for effectual recognition diseases using medical imaging tools. This study develops novel with optimal enabled skin lesion detection classification (CVOML-SLDC) model. The goal CVOML-SLDC model ...

Deep learning has played a major role in the interpretation of dermoscopic images for detecting skin defects and abnormalities. However, current deep solutions dermatological lesion analysis are typically limited providing probabilistic predictions which highlights importance concerning uncertainties. This concept uncertainty can provide confidence level each feature prevents overconfident with...

The prognosis for patients with skin cancer improves regular screening and checkups. Unfortunately, many people do not receive a diagnosis until the disease has advanced beyond point of effective therapy. Early detection is critical, automated diagnostic technologies like dermoscopy, an imaging device that detects lesions early in disease, are driving factor. lack annotated data class-imbalance...

This retrospective and exploratory study investigated the efficiency of 3T perfusion magnetic resonance imaging (MRI) at classification MS lesion subtypes. For subtype classification, firstly, it was necessary to segment all lesions. Therefore, a Bayesian classifier based on adaptive mixture method used lesions, an artificial neural network (ANN) employed multi-layer Perceptron as classifier. T...

INTRODUCTION: After the covid-19 outbreak, Monkeypox has become a global pandemic putting people’s lives in jeopardy. major concern 40+ countries apart from Africa as scientists are struggling to clinically diagnose virus it looks similar with chickenpox and measles. As part of our research, we found that get tested result monkey pox through polymerase chain reaction (PCR) test would take 3-4 d...