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Mortality Prediction

9 papers with code · Medical

Mortality prediction is the task of predicting the mortality of patients. It is important in medical decision support systems in order to prioritise the patients who have a high risk of mortality.

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Greatest papers with code

Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets

23 Oct 2017USC-Melady/Benchmarking_DL_MIMICIII

Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications.

LENGTH-OF-STAY PREDICTION MORTALITY PREDICTION SPEECH RECOGNITION TIME SERIES

Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

7 May 2019microsoft/horseshoe-bnn

However, flexible tools such as artificial neural networks (ANNs) suffer from a lack of interpretability limiting their acceptability to clinicians.

DECISION MAKING FEATURE SELECTION MORTALITY PREDICTION

Early hospital mortality prediction using vital signals

18 Mar 2018RezaSadeghiWSU/Early-Hospital-Mortality-Prediction-using-Vital-Signals

In order to predict the risk, quantitative features have been computed based on the heart rate signals of ICU patients.

MORTALITY PREDICTION

ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU

24 Jan 2019williamcaicedo/ISeeU

Nevertheless, a main impediment for the adoption of Deep Learning in healthcare is its reduced interpretability, for in this field it is crucial to gain insight on the why of predictions, to assure that models are actually learning relevant features instead of spurious correlations.

MORTALITY PREDICTION

Dynamic Measurement Scheduling for Event Forecasting using Deep RL

24 Jan 2019zzzace2000/autodiagnosis

We answer this question by deep reinforcement learning (RL) that jointly minimizes the measurement cost and maximizes predictive gain, by scheduling strategically-timed measurements.

MORTALITY PREDICTION

Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks

2 Aug 2019MLforHealth/MIMIC_Generalisation

When training clinical prediction models from electronic health records (EHRs), a key concern should be a model's ability to sustain performance over time when deployed, even as care practices, database systems, and population demographics evolve.

LENGTH-OF-STAY PREDICTION MORTALITY PREDICTION

Evaluation of Embeddings of Laboratory Test Codes for Patients at a Cancer Center

22 Jul 2019elleros/DSHealth2019_loinc_embeddings

Laboratory test results are an important and generally high dimensional component of a patient's Electronic Health Record (EHR).

MORTALITY PREDICTION