Publications by authors named "G K MENON"
Background: Verbal autopsy (VA) has been a crucial tool in ascertaining population-level cause of death (COD) estimates, specifically in countries where medical certification of COD is relatively limited. The World Health Organization has released an updated instrument (Verbal Autopsy Instrument 2022) that supports electronic data collection methods along with analytical software for assigning COD. This questionnaire encompasses the primary signs and symptoms associated with prevalent diseases across all age groups.
View Article and Find Full Text PDFBackground: Cause-of-death (CoD) information is crucial for health policy formulation, planning, and program implementation. Verbal Autopsy (VA) is an approach employed for the collection and analysis of CoD estimates at the population level where medical certification of cause of death is low and, secondly, for integrating it with the existing public health system by utilizing the grassroots level workforce.
Objective: The study aims to understand the field perspectives on implementing the 2022 WHO VA instrument in rural India through the existing public health system.
BharatSim is an open-source agent-based modelling framework for the Indian population. It can simulate populations at multiple scales, from small communities to states. BharatSim uses a synthetic population created by applying statistical methods and machine learning algorithms to survey data from multiple sources, including the Census of India, the India Human Development Survey, the National Sample Survey, and the Gridded Population of the World.
View Article and Find Full Text PDFArticle Synopsis
- Brain tumors are challenging to diagnose and classify in oncology, and radiomics—an emerging field that analyzes quantitative features from medical images—may improve treatment planning despite concerns about study methodologies.
- A systematic review of literature identified 18 studies using radiomic features and machine learning models to classify gliomas, demonstrating their potential in distinguishing tumor subtypes and grades using various imaging techniques like MRI and PET/CT.
- The findings suggest that radiomics can achieve high classification accuracy that sometimes surpasses traditional diagnostic methods and the performance of less experienced radiologists, highlighting the need for further validation in clinical practice.