Predicting Patient Outcomes
6 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Predicting Patient Outcomes
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
Ward2ICU
Latest papers
Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples
mahmoodlab/mamba
•
•
Human tissue and its constituent cells form a microenvironment that is fundamentally three-dimensional (3D).
Predicting Patient Outcomes with Graph Representation Learning
EmmaRocheteau/eICU-GNN-LSTM
•
•
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.
Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit
EmmaRocheteau/eICU-LoS-prediction
•
•
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.
Attentive State-Space Modeling of Disease Progression
Models of disease progression are instrumental for predicting patient outcomes and understanding disease dynamics.
Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward
We present a proxy dataset of vital signs with class labels indicating patient transitions from the ward to intensive care units called Ward2ICU.
DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network
havakv/pycox
•
•
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.
