Alle Papers – Machine Learning im Gesundheitswesen

Diagnostic Analysis of Patients with Essential Hypertension Using Association Rule Mining

The great detectives: humans versus AI detectors in catching large language model-generated medical writing

Machine learning approach for confirmation of COVID-19 cases: positive, negative, death and release

Toward personalized care management of patients at risk

Diabetes Care and Management Using Electronic Medical Records: A Systematic Review

Barriers to Achieving Economies of Scale in Analysis of EHR Data

Hematoma Expansion Context Guided Intracranial Hemorrhage Segmentation and Uncertainty Estimation

Quantifying the impact of AI recommendations with explanations on prescription decision making

Adversarial Collaborative Auto-encoder for Top-N Recommendation

Expert system for predicting unstable angina based on Bayesian networks

Automatic ICD Coding via Interactive Shared Representation Networks with Self-distillation Mechanism

Large Scale Diagnostic Code Classification for Medical Patient Records

Recognition of medication information from discharge summaries using ensembles of classifiers

Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease

A Proposed Technique Using Machine Learning for the Prediction of Diabetes Disease through a Mobile App

Artificial Intelligence Can Effectively Predict Early Hematoma Expansion of Intracerebral Hemorrhage Analyzing Noncontrast Computed Tomography Image

Use of Generative Artificial Intelligence, Including Large Language Models Such as ChatGPT, in Scientific Publications: Policies of <i>KJR</i> and Prominent Authorities

Exploring scalable medical image encoders beyond text supervision

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Development of a three tiered cognitive hybrid machine learning algorithm for effective diagnosis of Alzheimer’s disease

A PSO-based deep learning approach to classifying patients from emergency departments

Visualizing Risk Prediction Models

A data-driven framework of typical treatment process extraction and evaluation

Edema Extension Distance

Usefulness of a decision tree model for the analysis of adverse drug reactions: Evaluation of a risk prediction model of vancomycin‐associated nephrotoxicity constructed using a data mining procedure