Alle Papers – Machine Learning im Gesundheitswesen

Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis

Fuzzy expert system for diagnosing diabetic neuropathy

Analysis of type 2 diabetes heterogeneity with a tree-like representation: insights from the prospective German Diabetes Study and the LURIC cohort

Identifying Predictors of Suicide in Severe Mental Illness: A Feasibility Study of a Clinical Prediction Rule (Oxford Mental Illness and Suicide Tool or OxMIS)

Deep Ensemble Learning Approaches in Healthcare to Enhance the Prediction and Diagnosing Performance: The Workflows, Deployments, and Surveys on the Statistical, Image-Based, and Sequential Datasets

Multimorbidity associated with functional independence among community-dwelling older people: a cross-sectional study in Southern China

Contrastive BiLSTM-enabled Health Representation Learning for Remaining Useful Life Prediction

Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise

Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI

Predicting Sequences of Clinical Events by Using a Personalized Temporal Latent Embedding Model

Artificial intelligence, machine learning, and deep learning in women’s health nursing

Creation of a new longitudinal corpus of clinical narratives

Automated and flexible identification of complex disease: building a model for systemic lupus erythematosus using noisy labeling

Multimorbidity patterns, all‐cause mortality and healthy aging in older English adults: Results from the English Longitudinal Study of Aging

Extraction of Geriatric Syndromes From Electronic Health Record Clinical Notes: Assessment of Statistical Natural Language Processing Methods

Adversarial MACE Prediction After Acute Coronary Syndrome Using Electronic Health Records

Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing

MLRDA: A Multi-Task Semi-Supervised Learning Framework for Drug-Drug Interaction Prediction

Identifying Sepsis Subphenotypes via Time-Aware Multi-Modal Auto-Encoder

Multimodal classification of Alzheimer's disease and mild cognitive impairment using custom MKSCDDL kernel over CNN with transparent decision-making for explainable diagnosis

Inherent Bias in Artificial Intelligence-Based Decision Support Systems for Healthcare

Interpretable clinical time-series modeling with intelligent feature selection for early prediction of antimicrobial multidrug resistance

CLARUS: An interactive explainable AI platform for manual counterfactuals in graph neural networks

The need for quantification of uncertainty in artificial intelligence for clinical data analysis: increasing the level of trust in the decision-making process

Personalised treatment for cognitive impairment in dementia: development and validation of an artificial intelligence model