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hlblade's Projects

aaamlp-cn icon aaamlp-cn

Approaching (Almost) Any Machine Learning Problem中译版,在线文档地址:https://ytzfhqs.github.io/AAAMLP-CN/

aki-prediction icon aki-prediction

Deep Learning Models for AKI Prediction on MIMIC-III and eICU database

apollo icon apollo

APOLLO is an Accurate and independently validated Prediction mOdel of Lower-grade gLiomas Overall survival

deepsurv icon deepsurv

DeepSurv is a deep learning approach to survival analysis.

demo-clustering-longitudinal-data icon demo-clustering-longitudinal-data

Supplementary materials for the manuscript "Clustering of longitudinal data: A tutorial on a variety of approaches" by N. G. P. Den Teuling, S.C. Pauws, and E.R. van den Heuvel (2021)

echo-mimiciii icon echo-mimiciii

Transthoracic echocardiography and mortality in sepsis: analysis of the MIMIC-III database

lctmtools icon lctmtools

Latent Class Trajectory Models: An R Package

midodrine-mimic-iv icon midodrine-mimic-iv

Descriptive & prescriptive analysis of the effects of Vasoconstrictive medication via MIMIC's database using Targeted Maximum Likelihood Estimation for Causal Inference & ML techniques

mimic3-benchmarks icon mimic3-benchmarks

Python suite to construct benchmark machine learning datasets from the MIMIC-III 💊 clinical database.

mimic3cancerpromin icon mimic3cancerpromin

This repository contains codes and queries for process mining of cancer treatment in MIMIC-III dataset.

mortality-prediction-covid19 icon mortality-prediction-covid19

This program is for mortality prediction of COVID19. Taken from HAIRLAB with some adjustment. Using Decision tree algorithm for this machine learning program

pammtools icon pammtools

Piece-wise exponential Additive Mixed Modeling tools

patient-mortality-prediction-using-lstm icon patient-mortality-prediction-using-lstm

## Patient Mortality Prediction Using LSTM 🏥🔍 Welcome to the Patient Mortality Prediction Using LSTM repository! This project combines medical insights with advanced deep learning techniques to forecast patient mortality based on pediatric intensive care unit (PICU) data.

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