Alle Papers – Machine Learning im Gesundheitswesen

Ensemble Knowledge Tracing: Modeling interactions in learning process

Data-driven knowledge acquisition, validation, and transformation into HL7 Arden Syntax

Artificial intelligence for dementia genetics and omics

TLEABLCNN: Brain and Alzheimer’s Disease Detection Using Attention-Based Explainable Deep Learning and SMOTE Using Imbalanced Brain MRI

Trie-based rule processing for clinical NLP: A use-case study of n-trie, making the ConText algorithm more efficient and scalable

Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea

MATRIX: a unique patient classification system.

The role of emotion in self-explanations by cognitive agents

A multi-task Gaussian process self-attention neural network for real-time prediction of the need for mechanical ventilators in COVID-19 patients

Factors associated with exacerbations among adults with asthma according to electronic health record data

Artificial Intelligence in Cardiology: Concepts, Tools and Challenges - “The Horse is the One Who Runs, You Must Be the Jockey”

Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models

Literature-Augmented Clinical Outcome Prediction

Risk Classification With an Adaptive Naive Bayes Kernel Machine Model

A deep learning-based early alzheimer’s disease detection using magnetic resonance images

Predicting hospital readmission risk in patients with COVID-19: A machine learning approach

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values

Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes

A few-shot disease diagnosis decision making model based on meta-learning for general practice

Postsurgical functional outcome prediction model using deep learning framework (Prediction One, Sony Network Communications Inc.) for hypertensive intracerebral hemorrhage

Modular Neural Networks for Medical Prognosis: Quantifying the Benefits of Combining Neural Networks for Survival Prediction

Cardiovascular disease/stroke risk stratification in deep learning framework: a review

Deep learning for understanding multilabel imbalanced Chest X-ray datasets

The Evaluation of Generative AI Should Include Repetition to Assess Stability

Validation of discrete time‐to‐event prediction models in the presence of competing risks