Hybrid Deep Learning Framework for Melanoma Diagnosis Using Dermoscopic Medical Images.

Melanoma, or skin cancer, is a dangerous form of cancer that is the major cause of the demise of thousands of people around the world. In recent years, deep learning has become more popular for analyzing and detecting these medical issues. In this paper, a hybrid deep learning approach has been proposed based on U-Net for image segmentation, Inception-ResNet-v2 for feature extraction, and the Vision Transformer model with a self-attention mechanism for refining the features for early and accurate diagnosis and classification of skin cancer.

Electronic and adsorption properties of halogen molecule X (X=F, Cl) adsorbed arsenene: First-principles study.

The geometry, electronic structure, and adsorption properties of halogen molecule X(X = F, Cl) on arsenene were investigated using first-principles calculations. The adsorption of molecules was considered at various sites and in various orientations on the pristine arsenene (p-As) surface. Both molecules show chemisorption and the crystal orbital Hamiltonian population (COHP) analysis reveals the formation of strong X-As bonds.

Smoking is a predominant risk factor for coronary artery disease among Indians.

Smoking has emerged as a predominant risk factor for coronary artery disease (CAD) in India, contributing significantly to the country's rising cardiovascular morbidity and mortality rates. The adverse effects of tobacco on cardiovascular health are well-documented, exacerbating a public health challenge in a nation with a high prevalence of smoking. Therefore, it is of interest to analyse the impact of smoking on the incidence and progression of coronary artery disease among the Indian population, emphasizing the need for targeted public health interventions to mitigate this risk factor.