implementation of the method presented in "Minimax Risk Classifiers for Mislabeled Data: a Study on Patient Outcome Prediction Tasks".
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Updated
Jul 23, 2024 - Python
implementation of the method presented in "Minimax Risk Classifiers for Mislabeled Data: a Study on Patient Outcome Prediction Tasks".
Continuous patient state attention model for addressing irregularity in electronic health records
Stata PRISM Score Calculation
A Machine Learning Approach for Predicting the Death Time and Mortality
This repository contains the code used for Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit (https://dl.acm.org/doi/10.1145/3450439.3451860).
This is implementation of my Masters thesis work and aims at predicting the patient mortality from the MIMIC-III v1.4 Database
A RNN Predictive Model for COVID-19 mortality prediction.
Submission for the WiDS 2020 Kaggle competition: Predicting ICU deaths using CatBoost, XGBoost and RandomForest classifiers and the MIT GOSSIS dataset
A Multimodal Transformer: Fusing Clinical Notes With Structured EHR Data for Interpretable In-Hospital Mortality Prediction
A machine learning tool that uses gene expression data to classify cancer types and predict mortality rates.
FDSML Course Project 2020/21
Lifespan prediction research for the Illinois Risk Lab.
Predicting Mortality among a Cohort of patients with Heart Failure
Schätzung und Prognose der Sterblichkeit der britischen Bevölkerung (Männer und Frauen) unter Verwendung von zwei verschiedene Modelle: das Modell von Lee-Carter und das Modell von Cairns Blake Dowd (CBD)
COVID-19 Critical Event Prediction Tools
Standard tools to compare and evaluate mortality forecasting methods
Joint work product with co-authors Chelsea Jin and Matthew Ye for at the virtual ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop held on Sept. 22-25, 2020. Data engineering support from Nick Barbour.
This repository includes the code and data used to produce the analysis of placebo tests to measure excess post-disaster mortality.
Code and Datasets for the paper "An Interpretable Risk Prediction Model for Healthcare with Pattern Attention", published on BMC Medical Informatics and Decision Making.
Time-Sensitive Deep Learning for ICU Outcome Prediction Without Variable Selection or Cleaning.
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