Code for analyses in "Obesity and risk of female reproductive disorders: A Mendelian Randomisation Study"
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Updated
Dec 19, 2024 - R
Code for analyses in "Obesity and risk of female reproductive disorders: A Mendelian Randomisation Study"
Code to reproduce analysis and figures for 'Genetic mapping of etiologic brain cell types for obesity' (Timshel, eLife 2020)
🍎 Pipeline for Processing SISVAN Microdata on Nutritional Status Monitoring in Brazil
ObMetrics is a Shiny app developed to facilitate the calculation of outcomes related to Metabolic Syndrome in pediatric populations. This repository contains documentation and licensing details for the application, which aims to provide a user-friendly interface for healthcare professionals and researchers.
Analysis of obesity levels using MCA with two approaches for quantitative variables.
This notebook presents a concise analysis for predicting obesity risk using machine learning models like Random Forest and XGBoost. Focused on identifying key factors influencing obesity through exploratory data analysis (EDA) and predictive modeling, the notebook offers insights into effective prevention strategies.
OCS (BP): Examine global patterns of obesity across rural and urban regions
Codes for the statistical analysis that investigates the impact of high-fat diet on gut microbiome and serotonergic gene expression in the raphe nuclei.
India's First Open-Source GLP-1 Weight Loss Platform | 8 Clinical Evidence Charts | STEP Trials + NFHS-5 + WHO Data | Doctor-Supervised Semaglutide Therapy | ICMR-NIN 2024 | indiafattofit.com
Estimation of Obesity Levels
[In Production] Adaptation of Nathaniel Daw's Two-Step Sequential Learning Task. Designed for a study of reward prediction for food with college undergraduates.
Python & R scripts collection for AdipoAtlas project
Unveiling adipose populations linked to metabolic health in obesity
Predicting a Person's Obesity Level Using Decision Tree, Naive Bayes, and KNN Algorithms
Repository to preview, describe, and link to multiple health-related Tableau dashboards.
Conducted research and developed a system under Dr Booma Poolan Marikannan on provisional analysis for obesity issues using numerous data mining techniques by using a past medical dataset from the Kaggle. Executed the project using tools such as PyCaret, Pandas, NumPy, Matplotlib, Seaborn, Scikit-Learn, and Pickle, and evaluated the classificat…
Analysis of Spatial and Temporal Data Course Final Project - Obesity Classification
Using D3, this repository takes the data from the US Census Bureau's 2014 ACS 1-year estimates and creates animated visualizations from it.
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