mjkleiman

3point_dashboard

AD_feature_optimization

Code for the paper "Screening for early-stage Alzheimer’s disease using optimized feature sets and machine learning" by Michael J. Kleiman, Elan Barenholtz, and James E. Galvin

GazeDepression

Depression (High/Low based on PHQ) prediction using gaze behavior

multimodel

prosdk-addons-python

PyGazeAnalyser

Analysis and high-level plotting toolbox for eye-tracking data

PyTrack

stochastiCV

A method of cross-validation based on scikit-learn that splits data into subsampling or k-folds splits (using random or assigned seed values) and then repeats the model multiple times using different seeds. This function enables a more statistical and scientific method of investigating model performance.

streamlineAD

PhD Dissertation -- Streamlining Alzheimer's disease detection in clinical settings

Task-Classification

Pilot study for Search v Judgement task classification using eye movements

mjkleiman/3point_dashboard

mjkleiman/AD_feature_optimization

Code for the paper "Screening for early-stage Alzheimer’s disease using optimized feature sets and machine learning" by Michael J. Kleiman, Elan Barenholtz, and James E. Galvin

mjkleiman/GazeDepression

Depression (High/Low based on PHQ) prediction using gaze behavior

mjkleiman/multimodel

mjkleiman/prosdk-addons-python

mjkleiman/PyGazeAnalyser

Analysis and high-level plotting toolbox for eye-tracking data

mjkleiman/PyTrack

mjkleiman/stochastiCV

A method of cross-validation based on scikit-learn that splits data into subsampling or k-folds splits (using random or assigned seed values) and then repeats the model multiple times using different seeds. This function enables a more statistical and scientific method of investigating model performance.

mjkleiman/streamlineAD

PhD Dissertation -- Streamlining Alzheimer's disease detection in clinical settings

mjkleiman/Task-Classification

Pilot study for Search v Judgement task classification using eye movements