ESC 365 - Predicting mortality of type-2 diabetes mellitus by applying machine learning to electronic medical records in the west of scotland and hong kong

ESC Professional Premium Access

Predicting mortality of type-2 diabetes mellitus by applying machine learning to electronic medical records in the west of scotland and hong kong

Session: Progress and challenges in artificial intelligence for cardiovascular risk assessment and diagnosis

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Miss N. Kaur (Glasgow, GB)

Event: ESC Congress 2024

Congress Presentation

Add to my library

About the speaker

Miss Narinder Kaur

University of Glasgow, Glasgow (United Kingdom of Great Britain & Northern Ireland)

0 follower

8 more presentations in this session

Importance and limits of cardiovascular risk factors on the prediction of SCD using machine learning approach.

Speaker: Professor X. Jouven (Paris, FR)

Fully automated artificial intelligence-based cine cardiac magnetic resonance image quantification

Speaker: Mr P. Mohammadi Kazaj (Bern, CH)

Preventing unnecessary echocardiograms in de novo patients referred to the cardiology outpatient clinic using electrocardiogram-based deep learning

Speaker: Mr B. Arends (Utrecht, NL)

Barriers and facilitators for implementation of AI algorithms for ECG analysis and triage in patients with chest pain

Speaker: Mr B. Arends (Utrecht, NL)

An explainable AI for trustworthy detection of atrial fibrillation on reduced lead ECGs in mobile applications

Speaker: Mr A. Hammer (Dresden, DE)

Access the full session

Progress and challenges in artificial intelligence for cardiovascular risk assessment and diagnosis

Speakers: Miss N. Kaur, Professor X. Jouven, Mr P. Mohammadi Kazaj, Mr B. Arends, Mr B. Arends...

About the event

ESC Congress 2024

30 August - 2 September 2024

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources

Explore sponsored resources