Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans.

Background: The hippocampus plays a crucial role in memory and is one of the first structures affected by Alzheimer's disease. Postmortem MRI offers a way to quantify the alterations by measuring the atrophy of the inner structures of the hippocampus. Unfortunately, the manual segmentation of hippocampal subregions required to carry out these measures is very time-consuming.

Assessment of Self-Medication Practices and Knowledge Among Medical Students in Chengalpattu District: A Cross-Sectional Study.

Introduction: The practice of self-medication is wherein individuals initiate the use of medications without consulting a healthcare professional. College life is a period marked by academic, social, and personal changes. Due to their greater freedom and the pressure of academic success, students face various health issues.

Magnetized electroosmotic drug delivery of Au-SiO2 nanocarriers through blood-based jeffrey hybrid nanofluid in a microchannel: Caputo Fabrizio derivative modeling.

Fractional calculus is emerging as a promising field to overcome the intricacies inherent in biological systems that prevent conventional techniques from producing optimal results. The present research emphasizes the impact of thermal radiation, chemical reactions, and radiation absorption on an electroosmotic magnetohydrodynamic (MHD) blood-based Jeffrey hybrid nanofluid flow in a microchannel, employing the novel Caputo-Fabrizio fractional calculus approach. This study is carried out on two models: ramped and constant boundary conditions with distinct zeta potentials.

A novel dual-staining method for cost-effective visualization and differentiation of microbial biofilms.

Microbial biofilms are intricate communities that pose significant challenges in clinical and microbiological settings due to their resistance to antibiotics and immune responses. Advanced microscopy techniques, such as scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM), and fluorescence microscopy, are often employed to visualize and differentiate between these biofilms. However, these methods are not feasible in all laboratories because of their high cost and complexity.

Object Detection and Classification Framework for Analysis of Video Data Acquired from Indian Roads.

Object detection and classification in autonomous vehicles are crucial for ensuring safe and efficient navigation through complex environments. This paper addresses the need for robust detection and classification algorithms tailored specifically for Indian roads, which present unique challenges such as diverse traffic patterns, erratic driving behaviors, and varied weather conditions. Despite significant progress in object detection and classification for autonomous vehicles, existing methods often struggle to generalize effectively to the conditions encountered on Indian roads.