Alle Papers – Machine Learning im Gesundheitswesen
104.164 Papers insgesamt · Seite 265 von 400
The ethics of machine learning-based clinical decision support: an analysis through the lens of professionalisation theory
Interpretable explanations of black box classifiers applied on medical images by meaningful perturbations using variational autoencoders
Learning (predictive) risk scores in the presence of censoring due to interventions
Semantic-enhanced neural collaborative filtering models in recommender systems
Construction of a semi-automatic ICD-10 coding system
Trustworthy and ethical AI-enabled cardiovascular care: a rapid review
Training calibration-based counterfactual explainers for deep learning models in medical image analysis
A systematic approach to enhance the explainability of artificial intelligence in healthcare with application to diagnosis of diabetes
A visual approach to explainable computerized clinical decision support
Temporal reasoning in medicine
CokeBERT: Contextual knowledge selection and embedding towards enhanced pre-trained language models
Validating a membership disclosure metric for synthetic health data
Augmented Curation of Clinical Notes from a Massive EHR System Reveals Symptoms of Impending COVID-19 Diagnosis
A Dense Network Approach with Gaussian Optimizer for Cardiovascular Disease Prediction
Monkey business
Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment
Explainable machine learning to predict long-term mortality in critically ill ventilated patients: a retrospective study in central Taiwan
Early prediction of clinical deterioration using data-driven machine-learning modeling of electronic health records
Pediatric diabetes prediction using deep learning
Efficient Bayesian task-level transfer learning
PDD Graph: Bridging Electronic Medical Records and Biomedical Knowledge Graphs via Entity Linking
Adaptive semi-supervised recursive tree partitioning: The ART towards large scale patient indexing in personalized healthcare
Methodological Guidelines and Recommendations for Efficient and Rational Governance of Patient Registries
What prevents us from reusing medical real-world data in research
Understanding Heart-Failure Patients EHR Clinical Features via SHAP Interpretation of Tree-Based Machine Learning Model Predictions