marymlucas
Data nerd, healthcare, Python, R, ML, wrangling all the things. Doctoral candidate at Drexel University College of Computing & Informatics.
Drexel UniversityPhiladelphia, PA
marymlucas's Stars
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
salesforce/Merlion
Merlion: A Machine Learning Framework for Time Series Intelligence
synthetichealth/synthea
Synthetic Patient Population Simulator
thepanacealab/covid19_twitter
Covid-19 Twitter dataset for non-commercial research use and pre-processing scripts - under active development
MLforHealth/MIMIC_Extract
MIMIC-Extract:A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
MIT-LCP/eicu-code
Code and website related to the eICU Collaborative Research Database
mayoverse/arsenal
An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
almost-matching-exactly/DAME-FLAME-Python-Package
A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data
KenSciResearch/fairMLHealth
Healthcare-specific tools for bias analysis
epierson9/pain-disparities
WHOequity/HEAT
irenetrampoline/mimic-disparities
Plots from "Can AI Help Reduce Disparities in General Medical and Mental Health Care?"
MLD3/Deep-Learning-Applied-to-Chest-X-rays-Exploiting-and-Preventing-Shortcuts
[MLHC 2020] Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts (Jabbour, Fouhey, Kazerooni, Sjoding, Wiens). https://arxiv.org/abs/2009.10132
kevinlee1004/workshop_NLP
XDgov/MLBias
A growing set of resources on bias in data and machine learning/artificial intelligence in the federal government lives here.
almost-matching-exactly/AHB-R-package
AHB (Adaptive Hyper-box) R package provides two main algorithms: AHB_fast_match and AHB_MIP_match for Interpretable Individualized Treatment Effect Estimation.