Predicting Patient Outcomes

6 papers with code • 1 benchmarks • 1 datasets

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Most implemented papers

DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network

jaredleekatzman/DeepSurv 2 Jun 2016

We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations.

Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward

3778/Ward2ICU 2 Oct 2019

We present a proxy dataset of vital signs with class labels indicating patient transitions from the ward to intensive care units called Ward2ICU.

Attentive State-Space Modeling of Disease Progression

ahmedmalaa/attentive-state-space-models NeurIPS 2019

Models of disease progression are instrumental for predicting patient outcomes and understanding disease dynamics.

Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit

EmmaRocheteau/eICU-LoS-prediction 18 Jul 2020

In this work, we propose a new deep learning model based on the combination of temporal convolution and pointwise (1x1) convolution, to solve the length of stay prediction task on the eICU and MIMIC-IV critical care datasets.

Predicting Patient Outcomes with Graph Representation Learning

EmmaRocheteau/eICU-GNN-LSTM 11 Jan 2021

Recent work on predicting patient outcomes in the Intensive Care Unit (ICU) has focused heavily on the physiological time series data, largely ignoring sparse data such as diagnoses and medications.

Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples

mahmoodlab/mamba 27 Jul 2023

Human tissue and its constituent cells form a microenvironment that is fundamentally three-dimensional (3D).