INTRODUCTION: The Danish Health Care Registers rely on the International Statistical Classification of Diseases and Related Health Problems (ICD)-classification and stand as a widely utilized resource for health epidemiological research. Eating disor...
BACKGROUND: Stroke is a significant global health concern, ranking as the second leading cause of death and placing a substantial financial burden on healthcare systems, particularly in low- and middle-income countries. Timely evaluation of stroke se...
Clinical risk scores that predict outcomes in patients with atrial fibrillation (AF) have modest predictive value. Machine learning (ML) may achieve greater results when predicting adverse outcomes in patients with recently diagnosed AF. Several ML m...
The digitization of health records and growing availability of tumour DNA sequencing provide an opportunity to study the determinants of cancer outcomes with unprecedented richness. Patient data are often stored in unstructured text and siloed datase...
The spine journal : official journal of the North American Spine Society
39505010
BACKGROUND: Dysphonia is one of the more common complications following anterior cervical discectomy and fusion (ACDF). ACDF is the gold standard for treating degenerative cervical spine disorders, and identifying high-risk patients is therefore cruc...
The UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool, developed using advanced artificial intelligence (AI), significantly enhances the prediction of outcomes for deceased-donor kidney transplants in the UK. This study analyzed d...
This paper describes the use of digital solutions to improve the care of trauma patients in Germany. The focus is on the trauma networks of the German Society for Trauma Surgery (Deutsche Gesellschaft für Unfallchirurgie, DGU). The use of digital sol...
BACKGROUND: Decision tree algorithms, obtained by machine learning, provide clusters of patients with similar clinical patterns by the identification of variables that best merge with a given dependent variable.
BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implantation emphasize the importance of accurately assessing patients' risk before surgery. This study assesses the Machine Learning Assessment of Risk and E...
BACKGROUND: We present an automated image ingestion pipeline for a knee radiography registry, integrating a multilabel image-semantic classifier with conformal prediction-based uncertainty quantification and an object detection model for knee hardwar...