Alle Papers – Machine Learning im Gesundheitswesen

CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19

Prognostic Bayesian networks

LSTM for septic shock: Adding unreliable labels to reliable predictions

Limitations of large language models in clinical problem-solving arising from inflexible reasoning

Cox Proportional Hazard Regression Versus a Deep Learning Algorithm in the Prediction of Dementia: An Analysis Based on Periodic Health Examination

An alternative evaluation of post traumatic stress disorder with machine learning methods

Applications of deep learning methods in digital biomarker research using noninvasive sensing data

Comparing ChatGPT and clinical nurses’ performances on tracheostomy care: A cross-sectional study

Explainable AI: To Reveal the Logic of Black-Box Models

Data science in neurodegenerative disease: its capabilities, limitations, and perspectives

Three-Dimensional Convolutional Autoencoder Extracts Features of Structural Brain Images With a “Diagnostic Label-Free” Approach: Application to Schizophrenia Datasets

Big Data Science and Its Applications in Health and Medical Research: Challenges and Opportunities

A Drug Recommendation System for Multi-disease in Health Care Using Machine Learning

Deep Learning to Improve Heart Disease Risk Prediction

Healthcare predictive analytics for disease progression: a longitudinal data fusion approach

Deep Learning‐Based Ensembling Technique to Classify Alzheimer’s Disease Stages Using Functional MRI

Dataset Regeneration for Sequential Recommendation

Improving condition severity classification with an efficient active learning based framework

An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning

Learning Imaging Biomarker Trajectories from Noisy Alzheimer’s Disease Data Using a Bayesian Multilevel Model

Multisite implementation of a workflow-integrated machine learning system to optimize COVID-19 hospital admission decisions

Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches

Identifying Data Quality Dimensions for Person-Generated Wearable Device Data: Multi-Method Study

EMERGE-A Data-Driven Medical Decision Making Aid

Developing a shared sepsis data infrastructure: a systematic review and concept map to FHIR