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bkhundrakpam/README.md

Data scientist with extensive experience in healthcare and social science domains

Machine Learning applications in Health and Disease

  1. Built an accurate prediction model of autism severity with ~26% explained variance compared to ~13% explained variance in previous models, using a combination of partial least squares, support vector regression and elastic-net penalized linear regression in MATLAB (details in Moradi, Khundrakpam et al. NeuroImage 2017)
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  2. Built a predictive model of cognition with ~37% explained variance compared to 16% explained variance in previous models, using random forest regression in MATLAB (details at https://doi.org/10.1101/2021.07.05.451172)

  3. Built a predictive model of chronological age with ~70% explained variance compared to 45% explained variance in previous models, using elastic net penalized linear regression model in MATLAB (details in Khundrakpam et al. NeuroImage 2015)

Multivariate analysis of social environmental factors, brain and mental health

  1. Built multivariate models of social environmental factors and multi-modal brain data using canonical correlation analysis (CCA) and partial least squares (PLS) of a large sample of population dataset (12,000 individuals comprising of social environmental and neuroimaging data) in MATLAB

Pinned

  1. Analysis-of-brain-trajectories Analysis-of-brain-trajectories Public

    Analysis of brain trajectories using general linear models in health and disease

    MATLAB 1

  2. MLproject_Iris_Classification MLproject_Iris_Classification Public

    Classic classification of Iris dataset using various ML techniques

    Jupyter Notebook

  3. Stroke_prediction_using_SVM Stroke_prediction_using_SVM Public

    Predicting stroke using SVM and Logistic Regression

    Jupyter Notebook