rohankhera

AI-ECG-Chagas

awesome-ehr-deeplearning

Curated list of awesome papers for electronic health records(EHR) mining, machine learning, and deep learning.

clinical-longformer

CommonDataModel

Definition and DDLs for the OMOP Common Data Model (CDM)

COVID-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

covid-phenotyping-share

cTAKES-Python-API

cTAKES Python API interface for the Default Clinical Pipeline

CTGAN

Conditional GAN for generating synthetic tabular data.

PythonForSASUsers

An Introduction to Python for SAS Users

rohankhera/AI-ECG-Chagas

rohankhera/awesome-ehr-deeplearning

Curated list of awesome papers for electronic health records(EHR) mining, machine learning, and deep learning.

rohankhera/clinical-longformer

rohankhera/CommonDataModel

Definition and DDLs for the OMOP Common Data Model (CDM)

rohankhera/COVID-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

rohankhera/covid-phenotyping-share

rohankhera/CTGAN

Conditional GAN for generating synthetic tabular data.

rohankhera/deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

rohankhera/dicom-server

OSS Implementation of DICOMweb standard

rohankhera/docker-stacks

Ready-to-run Docker images containing Jupyter applications

rohankhera/ecg_plot

Plot standard multi lead ECG/EKG chart with Python

rohankhera/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

rohankhera/ETL-Synthea

Conversion from Synthea CSV to OMOP CDM

rohankhera/grf

Generalized Random Forests

rohankhera/handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

rohankhera/Legend

An R package implementing Large-Scale Evidence Generation and Evaluation in a Network of Databases (LEGEND).

rohankhera/LegendDiabetes

rohankhera/markdown-cheatsheet

Markdown Cheatsheet for Github Readme.md

rohankhera/mimic-code

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

rohankhera/ndc_map

Mapping U.S. FDA National Drug Codes (NDC) to Drug Classes and Codes

rohankhera/public_ep

rohankhera/roc

rohankhera/rohankhera

Config files for my GitHub profile.

rohankhera/ShinyDeploy

Shiny apps in this repository will be automatically deployed to the OHDSI Shiny server.

rohankhera/simclr

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

rohankhera/SkeletonComparativeEffectStudy

An R package that can be used as the starting point to implement a comparative effectiveness study.

rohankhera/tableone

Create "Table 1" for research papers in Python

rohankhera/tabnet

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

rohankhera/tutorials

PyTorch tutorials.

rohankhera/WhiteRabbit

WhiteRabbit is a small application that can be used to analyse the structure and contents of a database as preparation for designing an ETL. It comes with RabbitInAHat, an application for interactive design of an ETL to the OMOP Common Data Model with the help of the the scan report generated by White Rabbit.