Analysis of DWT-DCT watermarking algorithm on digital medical imaging.

Purpose: Over the past decade, the diagnostic information of the patients are digitally recorded and transferred. During the transmission of patients data, the security and authenticity of the information has to be ensured. Medical image watermarking technology has recently advanced because it can be used to conceal patient information while ensuring the authenticity.

Evaluating ChatGPT as a self-learning tool in medical biochemistry: A performance assessment in undergraduate medical university examination.

The emergence of ChatGPT as one of the most advanced chatbots and its ability to generate diverse data has given room for numerous discussions worldwide regarding its utility, particularly in advancing medical education and research. This study seeks to assess the performance of ChatGPT in medical biochemistry to evaluate its potential as an effective self-learning tool for medical students. This evaluation was carried out using the university examination question papers of both parts 1 and 2 of medical biochemistry which comprised theory and multiple choice questions (MCQs) accounting for a total of 100 in each part.

Pixel Intensity Resemblance Measurement and Deep Learning Based Computer Vision Model for Crack Detection and Analysis.

This research article is aimed at improving the efficiency of a computer vision system that uses image processing for detecting cracks. Images are prone to noise when captured using drones or under various lighting conditions. To analyze this, the images were gathered under various conditions.

Effect of webinars in teaching-learning process in medical and allied health science students during COVID-19 pandemic: A cross-sectional study.

Background: COVID-19 pandemic lockdown has brought all sectors to be dwindled with no exception of the academic system. Even professional courses like medical and allied health academic courses were also not spared. The academic requirements were not met as required to do so.

Implications of endocrine-disrupting chemicals on polycystic ovarian syndrome: A comprehensive review.

Polycystic ovarian syndrome (PCOS) is a complex multifactorial disorder of unknown pathogenesis in which genetic and environmental factors contribute synergistically to its phenotypic expressions. Endocrine-disrupting chemicals (EDCs), a group of widespread pollutants freely available in the environment and consumer products, can interfere with normal endocrine signals. Extensive evidence has shown that EDCs, environmental contributors to PCOS, can frequently induce ovarian and metabolic abnormalities at low doses.