Alle Papers – Machine Learning im Gesundheitswesen

Addressing Data Bias Problems for Chest X-ray Image Report Generation

Machine Learning in Predicting Diabetes in the Early Stage

Artificial Intelligence and Integrated Genotype–Phenotype Identification

Machine Learning-Based Cardiac Arrest Prediction for Early Warning System

Pre-training in Medical Data: A Survey

Large language models leverage external knowledge to extend clinical insight beyond language boundaries

Predicting Mortality in the Surgical Intensive Care Unit Using Artificial Intelligence and Natural Language Processing of Physician Documentation

Peeking into the Black Box: An Actuarial Case Study for Interpretable Machine Learning

Morphological characteristics of spoken language in schizophrenia patients – an exploratory study

Detecting Alzheimer’s Disease Using Machine Learning Methods

On the Application of Formal Methods to Clinical Guidelines, an Artificial Intelligence Perspective

Data-driven methodology to predict the ICU length of stay: A multicentre study of 99,492 admissions in 109 Brazilian units

Future Personal Health Records as a Foundation for Computational Health

Predicting Brain Age at Slice Level: Convolutional Neural Networks and Consequences for Interpretability

Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning

Prediction of 3-year all-cause and cardiovascular cause mortality in a prospective percutaneous coronary intervention registry: Machine learning model outperforms conventional clinical risk scores

Risk factor refinement and ensemble deep learning methods on prediction of heart failure using real healthcare records

DISCOVERING PATIENT PHENOTYPES USING GENERALIZED LOW RANK MODELS

Explaining deep learning for ECG analysis: Building blocks for auditing and knowledge discovery

Could prioritisation by emergency medicine dispatchers be improved by using computer-based decision support? A cohort of patients with chest pain

Exploiting complex medical data with interpretable deep learning for adverse drug event prediction

Concept-based electronic health records

Integrating Electronic Medical Records and Claims Data for Influenza Vaccine Research

Brain Hemorrhage Classification in CT Scan Images Using Minimalist Machine Learning

Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks