Alle Papers – Machine Learning im Gesundheitswesen

Large Language Models in Traditional Chinese Medicine: A Scoping Review

The treatment episode data set (TEDS)

Deep neural network model for enhancing disease prediction using auto encoder based broad learning

HIOC: a hybrid imputation method to predict missing values in medical datasets

An eXplainability Artificial Intelligence approach to brain connectivity in Alzheimer's disease

Quantifying Mental Health from Social Media with Neural User Embeddings

An NLP-based cognitive system for disease status identification in electronic health records

Predictive Intelligent Decision Support Model in Forecasting of the Diabetes Pandemic Using a Reinforcement Deep Learning Approach

Evaluation of the integration of retrieval-augmented generation in large language model for breast cancer nursing care responses

Testing and Evaluation of Generative Large Language Models in Electronic Health Record Applications: A Systematic Review

Physician clinical decision modification and bias assessment in a randomized controlled trial of AI assistance

Temporal information extraction from mental health records to identify duration of untreated psychosis

Combining Text Classification and Hidden Markov Modeling Techniques for Structuring Randomized Clinical Trial Abstracts

Impact of a Cardiology Data Bank on Physicians' Prognostic Estimates

Enhancing PCORnet Clinical Research Network data completeness by integrating multistate insurance claims with electronic health records in a cloud environment aligned with CMS security and privacy requirements

Medicine Expenditure Prediction via a Variance- Based Generative Adversarial Network

HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs

An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals

Leveraging Deep Learning for Designing Healthcare Analytics Heuristic for Diagnostics

Comparison of Automated Sepsis Identification Methods and Electronic Health Record–based Sepsis Phenotyping: Improving Case Identification Accuracy by Accounting for Confounding Comorbid Conditions

Using case-level context to classify cancer pathology reports

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms

Systems Medicine 2.0: Potential Benefits of Combining Electronic Health Care Records With Systems Science Models

Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study

Prediction of incident atrial fibrillation in community-based electronic health records: a systematic review with meta-analysis