Alle Papers – Machine Learning im Gesundheitswesen

Comparing conventional statistical models and machine learning in a small cohort of South African cardiac patients

The artificial intelligence (AI) revolution: How important for scientific work and its reliable sharing

Conceptual design of a generic data harmonization process for OMOP common data model

Does Multimorbidity Influence the Occurrence Rates of Chronic Conditions? A Claims Data Based Comparison of Expected and Observed Prevalence Rates

Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness

Recognition-based diagnostic reasoning

Systematic evaluation of common natural language processing techniques to codify clinical notes

An Efficient Framework to Detect Intracranial Hemorrhage Using Hybrid Deep Neural Networks

Accuracy assessment of prediction in patient outcomes

Artificial Intelligence in Medicine

A multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis

Artificial Intelligence in Healthcare Competition (TEKNOFEST-2021): Stroke Data Set

Combining LSTM and Latent Topic Modeling for Mortality Prediction

Multi Chronic Disease Prediction System Using CNN and Random Forest

Establishment of a model for predicting preterm birth based on the machine learning algorithm

Local large language models for privacy-preserving accelerated review of historic echocardiogram reports

Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort electronic health records

Methods Used in the Development of Common Data Models for Health Data: Scoping Review

REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers

A Federated Learning based Approach for Heart Disease Prediction

Emulate randomized clinical trials using heterogeneous treatment effect estimation for personalized treatments: Methodology review and benchmark

Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)

Using Electronic Medical Record to Identify Patients With Dyslipidemia in Primary Care Settings: International Classification of Disease Code Matters From One Region to a National Database

Identifying epilepsy psychiatric comorbidities with machine learning

Low-Rank Sparse Feature Selection for Patient Similarity Learning