Alle Papers – Machine Learning im Gesundheitswesen

RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?

Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients

Application of Neural Network and Cluster Analyses to Differentiate TCM Patterns in Patients With Breast Cancer

Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives.

A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment

Cybersecurity in the generative artificial intelligence era

Improved biomedical word embeddings in the transformer era

Benchmarking the Confidence of Large Language Models in Answering Clinical Questions: Cross-Sectional Evaluation Study

Beyond Post hoc Explanations: A Comprehensive Framework for Accountable AI in Medical Imaging Through Transparency, Interpretability, and Explainability

Applying Deep Learning Model to Predict Diagnosis Code of Medical Records

A qualitative study of physician perspectives on adaptation to electronic health records

Using Deep Learning Based Natural Language Processing Techniques for Clinical Decision-Making with EHRs

Replication of Real-World Evidence in Oncology Using Electronic Health Record Data Extracted by Machine Learning

Machine-learning-based adverse drug event prediction from observational health data: A review

BITES: balanced individual treatment effect for survival data

Algorithmic bias in health care: Opportunities for nurses to improve equality in the age of artificial intelligence

Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis

Cognitive Screening in Persons With Chronic Diseases in Primary Care

A novel imputation method for effective prediction of coronary Kidney disease

ANEMIA: An expert consultation system

Knowledge-Rich Self-Supervision for Biomedical Entity Linking

Artificial Intelligence in the Intensive Care Unit: Current Evidence on an Inevitable Future Tool

Predicting the Mortality and Readmission of In-Hospital Cardiac Arrest Patients With Electronic Health Records: A Machine Learning Approach

Mental health assessment: Inference, explanation, and coherence

Novel Approach to Predict Hospital Readmissions Using Feature Selection from Unstructured Data with Class Imbalance