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The Case Records of ChatGPT: Language Models and Complex Clinical Questions
Results: GPT4 and GPT3. 5 accurately provided the correct diagnosis in 26% and 22% of cases in one attempt, and 46% and 42% within three attempts, respectively.
Bayesian Optimization of 2D Echocardiography Segmentation
Bayesian Optimization (BO) is a well-studied hyperparameter tuning technique that is more efficient than grid search for high-cost, high-parameter machine learning problems.
Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
The electrocardiogram (ECG) is a widely-used medical test, typically consisting of 12 voltage versus time traces collected from surface recordings over the heart.
Interpretable Neural Networks for Predicting Mortality Risk using Multi-modal Electronic Health Records
We present an interpretable neural network for predicting an important clinical outcome (1-year mortality) from multi-modal Electronic Health Record (EHR) data.
A deep neural network to enhance prediction of 1-year mortality using echocardiographic videos of the heart
We show that a large dataset of 723, 754 clinically-acquired echocardiographic videos (~45 million images) linked to longitudinal follow-up data in 27, 028 patients can be used to train a deep neural network to predict 1-year mortality with good accuracy (area under the curve (AUC) in an independent test set = 0. 839).
