Alle Papers – Machine Learning im Gesundheitswesen

Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data

Applications of Machine Learning in Palliative Care: A Systematic Review

Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning

Systematic comparison of 3D Deep learning and classical machine learning explanations for Alzheimer’s Disease detection

Three-stage intelligent support of clinical decision making for higher trust, validity, and explainability

Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients Using Primary Care Electronic Health Records

Mortality Prediction in Cerebral Hemorrhage Patients Using Machine Learning Algorithms in Intensive Care Units

Automated Ambulatory Medical Records Systems: <i>An Orphan Technology</i>

COSARA: Integrated Service Platform for Infection Surveillance and Antibiotic Management in the ICU

Crossing the “Cookie Theft” Corpus Chasm: Applying What BERT Learns From Outside Data to the ADReSS Challenge Dementia Detection Task

Improving rare disease classification using imperfect knowledge graph

Validity of clinical prediction rules for isolating inpatients with suspected tuberculosis

A visual analytics system for multi-model comparison on clinical data predictions

Uncovering interpretable potential confounders in electronic medical records

Clinical Decision Support Systems

GEMINI

Prediction of Patients with Heart Disease using Artificial Neural Network and Adaptive Boosting techniques

A fuzzy logic–based warning system for patients classification

A Comparison of Machine Learning Techniques for the Detection of Type-2 Diabetes Mellitus: Experiences from Bangladesh

Development and Validation of a Machine Learning Model for Automated Assessment of Resident Clinical Reasoning Documentation

An intelligent multimodal medical diagnosis system based on patients’ medical questions and structured symptoms for telemedicine

The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues

How to Safely Integrate Large Language Models Into Health Care

Regularizing Black-box Models for Improved Interpretability