Selected Publication:

SHR Neuro Cancer Cardio Lipid Metab Microb

Hussain, S; Raza, Z; Kumar, TVV; Goswami, N.
Diagnosing Neurally Mediated Syncope Using Classification Techniques.
J Clin Med. 2021; 10(21): Doi: 10.3390/jcm10215016 [OPEN ACCESS]
Web of Science PubMed FullText FullText_MUG

 

Co-authors Med Uni Graz

Goswami Nandu

Altmetrics:

Dimensions Citations:

Plum Analytics:

Scite (citation analytics):

Abstract:

Syncope is a medical condition resulting in the spontaneous transient loss of consciousness and postural tone with spontaneous recovery. The diagnosis of syncope is a challenging task, as similar types of symptoms are observed in seizures, vertigo, stroke, coma, etc. The advent of Healthcare 4.0, which facilitates the usage of artificial intelligence and big data, has been widely used for diagnosing various diseases based on past historical data. In this paper, classification-based machine learning is used to diagnose syncope based on data collected through a head-up tilt test carried out in a purely clinical setting. This work is concerned with the use of classification techniques for diagnosing neurally mediated syncope triggered by a number of neurocardiogenic or cardiac-related factors. Experimental results show the effectiveness of using classification-based machine learning techniques for an early diagnosis and proactive treatment of neurally mediated syncope.

Find related publications in this database (Keywords)

neuro mediated syncope

classification

machine learning

head-up tilt (HUT) test

© Med Uni Graz • Imprint