Alle Papers – Machine Learning im Gesundheitswesen

Detecting Latent Clinical Taxa by Fallible Quantitative Indicators Lacking an Accepted Criterion

Diagnostic Reasoning and Decision Making in the Context of Health Information Technology

Accessing routinely collected health data to improve clinical trials: recent experience of access

Machine Learning in Clinical Trials: A Primer with Applications to Neurology

A Review on Electronic Health Record Text-Mining for Biomedical Name Entity Recognition in Healthcare Domain

Graph Convolution Based Attention Model for Personalized Disease Prediction

Dynamical Phenotyping: Using Temporal Analysis of Clinically Collected Physiologic Data to Stratify Populations

Comparison of Deep Learning and Classical Machine Learning Algorithms to Predict Postoperative Outcomes for Anterior Cervical Discectomy and Fusion Procedures With State-of-the-art Performance

Machine-learning model to predict the cause of death using a stacking ensemble method for observational data

Statistical Prediction Models, Artificial Neural Networks, and the Sophism “I Am a Patient, Not a Statistic”

Using Artificial Intelligence to Improve Primary Care for Patients and Clinicians

Machine Learning in Medical Emergencies: a Systematic Review and Analysis

Using data mining techniques to characterize participation in observational studies

Large Language Models for More Efficient Reporting of Hospital Quality Measures

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks

A review on deep neural networks for ICD coding

Neural networks for mining the associations between diseases and symptoms in clinical notes

EHR-based Visualization Tool: Adoption Rates, Satisfaction, and Patient Outcomes

Attention-based multimodal fusion with contrast for robust clinical prediction in the face of missing modalities

Hierarchical Attention Propagation for Healthcare Representation Learning

Database queries for hospitalizations for acute congestive heart failure: flexible methods and validation based on set theory

Prediction of short-term atrial fibrillation risk using primary care electronic health records

Application of Artificial Intelligence for Medical Research

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records

Early Prediction of Sepsis From Clinical Data Using Ratio and Power-Based Features