Work

Artificial Neural Network Model in Stroke Diagnosis

Year: 2015

Type: conference-paper

Abstract: We present a model of Artificial Neural Network (ANN) applied to stroke diagnosis. We use input data related to stroke that serves as inputs for the ANN. These data include clinical symptoms together with stroke risk factors. Each type of data provides input that is evaluated and used during the ANN processing. The adaptive learning algorithm can be used with a plethora of types of medical data and integrated into categorized outputs.

Source: UKSim International Conference on Computer Modelling and Simulation (UKSim)

DOI: 10.1109/uksim.2015.33

Authors: Lela Mirtskhulava, Julian Wong, Salah Al-Majeed, Gillian Pearce

Institutions: Tbilisi State University, Military Technological College, National University Heart Centre Singapore, Aston University

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2490950022