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.

Toward Efficient Bactericidal and Dye Degradation Performance of Strontium- and Starch-Doped FeO Nanostructures: In Silico Molecular Docking Studies.

In this study, various concentrations of strontium (Sr) into a fixed amount of starch (St) and FeO nanostructures (NSs) were synthesized with the co-precipitation approach to evaluate the antibacterial and photocatalytic properties of the concerned NSs. The study aimed to synthesize nanorods of FeO with co-precipitation to enhance the bactericidal behavior with dopant-dependent FeO. Advanced techniques were utilized to investigate the structural characteristics, morphological properties, optical absorption and emission, and elemental composition properties of synthesized samples.

Photocatalytic and antibacterial activity of graphene oxide/cellulose-doped TiO quantum dots: molecular docking studies.

Graphene oxide (GO) and cellulose nanocrystal (CNC)-doped TiO quantum dots (QDs) were effectively synthesized by employing the co-precipitation method for the degradation of dyes and antimicrobial applications. A series of characterizations, , XRD, FTIR, UV-visible spectroscopy, EDS, FE-SEM, and HR-TEM, was used to characterize the prepared samples. A reduction in PL intensity was observed, while the band gap energy ( ) decreased from 3.

Improved catalytic activity and bactericidal behavior of novel chitosan/VO co-doped in tin-oxide quantum dots.

The novel VO/chitosan (CS) co-doped tin oxide (SnO) quantum dots (QDs) were synthesized co-precipitation technique. The optical, structural, morphological, and catalytic properties of the concerned specimens were examined by UV-Vis, PL, FTIR, X-ray diffraction, HR-TEM, and EDS. Structural analysis through XRD confirmed the tetragonal structure of SnO; meanwhile, HR-TEM measurements unveiled quantum dot morphology.

Deep Learning Approach for Automatic Microaneurysms Detection.

In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness.