Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.]

The prediction of heart diseases is a crucial aspect of healthcare, as it helps medical professionals to diagnose and treat the condition at an early stage. This is a preliminary study that aims to investigate the Random Forest Algorithm (RFA) that accurately predicts the presence of heart diseases,...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Suhaidin, Muhammad Iqbal (Auteur), Mohamed Yusoff, Syarifah Adilah (Auteur), Johan, Elly Johana (Auteur), Mydin, Azlina (Auteur), Wan Mohamad, Wan Anisha (Auteur)
Format: Livre
Publié: Unit Penerbitan JSKM, 2023-04.
Sujets:
Accès en ligne:Link Metadata
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

MARC

LEADER 00000 am a22000003u 4500
001 repouitm_83497
042 |a dc 
100 1 0 |a Suhaidin, Muhammad Iqbal  |e author 
700 1 0 |a Mohamed Yusoff, Syarifah Adilah  |e author 
700 1 0 |a Johan, Elly Johana  |e author 
700 1 0 |a Mydin, Azlina  |e author 
700 1 0 |a Wan Mohamad, Wan Anisha  |e author 
245 0 0 |a Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.] 
260 |b Unit Penerbitan JSKM,   |c 2023-04. 
500 |a https://ir.uitm.edu.my/id/eprint/83497/1/83497.pdf 
520 |a The prediction of heart diseases is a crucial aspect of healthcare, as it helps medical professionals to diagnose and treat the condition at an early stage. This is a preliminary study that aims to investigate the Random Forest Algorithm (RFA) that accurately predicts the presence of heart diseases, enabling healthcare providers to take proactive measures to prevent severe health complications and improve patient outcomes. RFA as a machine learning classification model has the potential to provide more accurate predictions than traditional methods. This potential has been investigated by thoroughly compared with several other studies across implementation of different types of dataset and algorithms. Furthermore, additional prototypes could be used in clinical settings, providing valuable insights to healthcare providers and contributing to the advancement of medical research 
546 |a en 
690 |a Evolutionary programming (Computer science). Genetic algorithms 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/83497/ 
787 0 |n https://appspenang.uitm.edu.my/sigcs/ 
856 4 1 |u https://ir.uitm.edu.my/id/eprint/83497/  |z Link Metadata