Optimization of HIV drugs through MCDM technique Analytic Hierarchy Process(AHP).

Topological indices are crucial tools for predicting the physicochemical and biological features of different drugs. They are numerical values obtained from the structure of chemical molecules. These indices, particularly the degree-based TIs are a useful tools for evaluating the connection between a compound's structure and its attributes.

Bridging the Gap: The Importance of Non-technical Skills in Cardiology for Enhanced Patient Care and Team Performance.

Cardiology, a high-acuity medical specialty, has traditionally emphasised technical expertise, often overshadowing the critical role of non-technical skills (NTS). This imbalance stems from the historical focus on procedural competence and clinical knowledge in cardiology training and practice, leaving a significant gap in the development of crucial interpersonal and cognitive abilities. However, emerging evidence highlights the significant impact of NTS on patient outcomes, team dynamics, and overall healthcare efficiency.

Impact of Kidney Disease in Patients Undergoing Catheter Directed Interventions for Intermediate to High-Risk Pulmonary Embolism.

Background: Catheter-directed interventions (CDIs) for pulmonary embolism (PE) continue to evolve. However, due to the paucity of data, their use has been limited in patients with underlying kidney disease.

Methods: The National Readmission Database (2016-2020) was utilized to identify intermediate to high-risk PE (IHR-PE) patients requiring CDI (thrombectomy, thrombolysis, and ultrasound-assisted thrombolysis).

A computational approach to drug design for multiple sclerosis via QSPR modeling, chemical graph theory, and multi-criteria decision analysis.

Multiple sclerosis (MS) is a complex autoimmune disease of the central nervous system with an unknown etiology. While disease-modifying therapies can slow progression, there is a need for more effective treatments. Quantitative structure-activity relationship (QSAR) modeling using topological indices derived from chemical graph theory is a promising approach to rationally design new drugs for MS.

Deep learning-based automation for segmentation and biometric measurement of the gestational sac in ultrasound images.

Introduction: Monitoring the morphological features of the gestational sac (GS) and measuring the mean sac diameter (MSD) during early pregnancy are essential for predicting spontaneous miscarriage and estimating gestational age (GA). However, the manual process is labor-intensive and highly dependent on the sonographer's expertise. This study aims to develop an automated pipeline to assist sonographers in accurately segmenting the GS and estimating GA.