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3dmrisegmentation

Code for NeuroImage: Clinical paper "Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network."

acute-stroke_detection_segmentation

adv

Antidepressants Variability Ratio Bayesian Meta-Analysis

ailab

Experience, Learn and Code the latest breakthrough innovations with Microsoft AI

anova-test-in-python

Analysis of Variance (ANOVA)

ards_plos_one_2019

Machine Learning for Patient Risk Stratification for Acute Respiratory Distress Syndrome (Zeiberg & Prahlad et al.), PLOS ONE, March 2019. https://doi.org/10.1371/journal.pone.0214465

audio-snr

Mixing an audio file with a noise file at any Signal-to-Noise Ratio (SNR)

automaticsleepstageclassifier

Sleep stage automatic classifier using CNNs and LSTMs to process frequency signals of brain activity recorded via ElectroEncephaloGram EEG. Undergraduate thesis

causal-quasi

clinicaltools

Clinical-AI Research Framework

codeweb.github.io

codeweb design responsive

computer-vision

context-aware-recommender

Hybrid Recommender System

datacamp

Datacamp notebooks

decision-rules-network

This repository contains the source code of the paper "Learning Accurate and Interpretable Decision Rule Sets from Neural Networks".

deep-learning-tutorials

ML_tutorials

deepsleepnet

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

emotion-recognition-using-speech

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

end2you

esm-parents-with-psychosis

R code used to analyse ESM (experience sampling methodology) data from a study measuring stress and psychosis in parents

facial-

finetune.github.io

ggdmc

Bayesian Cognitive Modelling

glassmorphism

Curriculum Vitae in Glassmorphism Style

haines_cvml_2018

Data and codes used for primary analyses in Haines et al. (2019, PLOS ONE) Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity

hbayesdm

Hierarchical Bayesian modeling of RLDM tasks, using R & Python

heart-failure-condition-and-survival-analysis

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

io

Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO

kaldi-for-dummies

This is the repository for my version of Kaldi for Dummies example.

mcse