This paper is in the following e-collection/theme issue:

Development and Evaluation of Research Methods, Instruments and Tools (511) Machine Learning (1501) Stroke (166) Clinical Information and Decision Making (1434) Clinical Informatics (1050) Tools, Programs and Algorithms (275)

Published on in Vol 5, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23440, first published .
Predicting Risk of Stroke From Lab Tests Using Machine Learning Algorithms: Development and Evaluation of Prediction Models

Predicting Risk of Stroke From Lab Tests Using Machine Learning Algorithms: Development and Evaluation of Prediction Models

Predicting Risk of Stroke From Lab Tests Using Machine Learning Algorithms: Development and Evaluation of Prediction Models

Authors of this article:

Eman M Alanazi1, 2 Author Orcid Image ;   Aalaa Abdou3 Author Orcid Image ;   Jake Luo4 Author Orcid Image
Article Authors Cited by (19) Tweetations (4) Metrics

Journals

  1. Kokkotis C, Giarmatzis G, Giannakou E, Moustakidis S, Tsatalas T, Tsiptsios D, Vadikolias K, Aggelousis N. An Explainable Machine Learning Pipeline for Stroke Prediction on Imbalanced Data. Diagnostics 2022;12(10):2392 View
  2. Alharthi N, Alanazi E, Liu X. Awareness Level of Huntington Disease: Comprehensive Analysis of Tweets During Huntington Disease Awareness Month. Computer Methods and Programs in Biomedicine Update 2023;4:100117 View
  3. Sasano T, Ihara K, Tanaka T, Furukawa T, Yuasa S. Risk stratification of atrial fibrillation and stroke using single nucleotide polymorphism and circulating biomarkers. PLOS ONE 2023;18(10):e0292118 View
  4. Okeibunor J, Jaca A, Iwu-Jaja C, Idemili-Aronu N, Ba H, Zantsi Z, Ndlambe A, Mavundza E, Muneene D, Wiysonge C, Makubalo L. The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review. Frontiers in Public Health 2023;11 View
  5. Abegaz T, Baljoon A, Kilanko O, Sherbeny F, Ali A. Machine learning algorithms to predict major adverse cardiovascular events in patients with diabetes. Computers in Biology and Medicine 2023;164:107289 View
  6. Abujaber A, Albalkhi I, Imam Y, Nashwan A, Akhtar N, Alkhawaldeh I. Machine learning-based prognostication of mortality in stroke patients. Heliyon 2024;10(7):e28869 View
  7. Hassan A, Gulzar Ahmad S, Ullah Munir E, Ali Khan I, Ramzan N. Predictive modelling and identification of key risk factors for stroke using machine learning. Scientific Reports 2024;14(1) View
  8. Shih D, Wu Y, Wu T, Chu H, Shih M. Stroke Prediction Using Deep Learning and Transfer Learning Approaches. IEEE Access 2024;12:130091 View
  9. Asadi F, Rahimi M, Daeechini A, Paghe A. The most efficient machine learning algorithms in stroke prediction: A systematic review. Health Science Reports 2024;7(10) View
  10. Abujaber A, Yaseen S, Imam Y, Nashwan A, Akhtar N. Machine learning-based prediction of one-year mortality in ischemic stroke patients. Oxford Open Neuroscience 2024;3 View
  11. Wei Y, Lin D, Lian Y, Wei Q, Zheng L, Yuan K, Zhao J, Kuang K, Tang Y, Gao Y. Population data study reveals pain as a possible protective factor against cerebrovascular disease in cancer patients. Scientific Reports 2024;14(1) View
  12. Swain K, Tak T, Upreti K, Kshirsagar P, Krishnan S, Poonia R, Nayak S, Mohanty M. Enhancing Stroke Prediction Using LightGBM With SMOTE-ENN and Fine-Tuning: A Comprehensive Analysis. Cureus Journals 2024 View

Books/Policy Documents

  1. Aissaoui F, Boudali I, Abdellatif T. Advances in Model and Data Engineering in the Digitalization Era. View