Alle Papers – Machine Learning im Gesundheitswesen

Counterfactual Supporting Facts Extraction for Explainable Medical Record Based Diagnosis with Graph Network

Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records

Healthcare Professionals’ Expectations of Medical Artificial Intelligence and Strategies for its Clinical Implementation: A Qualitative Study

Mapping scientific landscapes in UMLS research: a scientometric review

Learning Bayesian networks from survival data using weighting censored instances

Detection of cognitive impairment using a machine-learning algorithm

Interpreting the Predictions of Complex ML Models by Layer-wise\n Relevance Propagation

Optimal data systems

Identification of patients with carotid stenosis using natural language processing

Artificial Intelligence in Medicine

Classification Models to Predict Survival of Kidney Transplant Recipients Using Two Intelligent Techniques of Data Mining and Logistic Regression.

Contrastive Pre-training for Sequential Recommendation.

Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians

Multi-view singular value decomposition for disease subtyping and genetic associations

Recognition of Critical Situations from Time Series of Laboratory Results by Case-Based Reasoning

A New Real Time Clinical Decision Support System Using Machine Learning for Critical Care Units

SurvMaximin: Robust federated approach to transporting survival risk prediction models

Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge Assessments

Targeted Self Supervision For Classification On A Small Covid-19 Ct Scan Dataset

Predicting 30-day mortality of patients with pneumonia in an emergency department setting using machine-learning models

Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings

Diagnosis and Medicine Prediction for COVID-19 Using Machine Learning Approach

Cardiac Risk Stratification in Renal Transplantation Using a Form of Artificial Intelligence

Hard for humans, hard for machines: predicting readmission after psychiatric hospitalization using narrative notes

Utilizing dynamic treatment information for MACE prediction of acute coronary syndrome