The Diagnostic Efficacy of an App-based Diagnostic Health Care Application in the Emergency Room: eRadaR-Trial. A prospective, Double-blinded, Observational Study.

Objective: To evaluate the diagnostic accuracy of the app-based diagnostic tool Ada and the impact on patient outcome in the emergency room (ER).

Background: Artificial intelligence-based diagnostic tools can improve targeted processes in health care delivery by integrating patient information with a medical knowledge base and a machine learning system, providing clinicians with differential diagnoses and recommendations.

Methods: Patients presenting to the ER with abdominal pain self-assessed their symptoms using the Ada-App under supervision and were subsequently assessed by the ER physician.

Minimally Invasive Treatment of Kommerell's Diverticulum and Left Aberrant Subclavian Artery.

Kommerell's diverticulum is an aneurysmatic offspring of the left aberrant subclavian artery, which is a rare vascular anomaly of the aortic arch. Here, we present our less invasive approach to the repair of a symptomatic Kommerell's diverticulum in a 31-year-old patient, without the use of cardiopulmonary bypass.

Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial.

Introduction: Occurrence of inaccurate or delayed diagnoses is a significant concern in patient care, particularly in emergency medicine, where decision making is often constrained by high throughput and inaccurate admission diagnoses. Artificial intelligence-based diagnostic decision support system have been developed to enhance clinical performance by suggesting differential diagnoses to a given case, based on an integrated medical knowledge base and machine learning techniques. The purpose of the study is to evaluate the diagnostic accuracy of Ada, an app-based diagnostic tool and the impact on patient outcome.