Coati optimization algorithm for brain tumor identification based on MRI with utilizing phase-aware composite deep neural network.

Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues.

Advancing fetal ultrasound diagnostics: Innovative methodologies for improved accuracy in detecting down syndrome.

This research work explores the integration of medical and information technology, particularly focusing on the use of data analytics and deep learning techniques in medical image processing. Specifically, it addresses the diagnosis and prediction of fetal conditions, including Down Syndrome (DS), through the analysis of ultrasound images. Despite existing methods in image segmentation, feature extraction, and classification, there is a pressing need to enhance diagnostic accuracy.

Phytochemical profiling, human insulin stability and alpha glucosidase inhibition of Gymnema latifolium leaves aqueous extract: Exploring through experimental and in silico approach.

Diabetes mellitus Type 2 (DM2T) is a rapidly expanding metabolic endocrine disorder worldwide. It is caused due to inadequate insulin secretion by pancreatic beta cells as well as development of insulin resistance. This study aimed to investigate the anti-α-glucosidase, insulin stabilization effect, and non-cytotoxic nature of Gymnema latifolium leaf aqueous extract (GLAE).