Kavitha S

Abstract Accurate segmentation and optimal diagnosis are required for myocardial infarction (MI) because it is a life-threatening cardiovascular condition. Therefore, its quantification is necessary to facilitate accurate diagnosis and make beneficial decisions to prevent a heart attack. Advanced cutting-edge techniques, such as deep learning, promise more precise MI segmentation and potentially provide an automated segmentation of annotated cardiac MRI (CMRI) datasets.

Cancer cachexia is a multifactorial syndrome characterized by progressive loss of skeletal muscle mass, involuntary weight loss, anorexia, metabolic dysfunction, and systemic inflammation. It affects approximately 50–80% of patients with advanced malignancies and is particularly common in advanced non-small cell lung cancer (NSCLC), where it negatively influences treatment tolerance, quality of life, functional performance, and overall survival.

Intermittent and prolonged fasting have become increasingly recognized as effective nutritional interventions for improving metabolic health, insulin sensitivity, body composition, and overall well-being. Despite these benefits, hunger remains one of the principal barriers limiting adherence to fasting protocols.