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

Tutorial (78) Artificial Intelligence (2129) Machine Learning (2076) Advanced Data Analytics in eHealth (209) Decision Support for Health Professionals (1539) Clinical Information and Decision Making (1915)

Published on in Vol 25 (2023)

This is a member publication of University of Cambridge (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49949, first published .
Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial

Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial

Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial

Authors of this article:

Arun James Thirunavukarasu1, 2 Author Orcid Image ;   Kabilan Elangovan2 Author Orcid Image ;   Laura Gutierrez2 Author Orcid Image ;   Yong Li2 Author Orcid Image ;   Iris Tan2 Author Orcid Image ;   Pearse A Keane3 Author Orcid Image ;   Edward Korot4, 5 Author Orcid Image ;   Daniel Shu Wei Ting2, 4, 6 Author Orcid Image
Article Authors Cited by (25) Tweetations (5) Metrics

Journals

  1. Ng F, Thirunavukarasu A, Cheng H, Tan T, Gutierrez L, Lan Y, Ong J, Chong Y, Ngiam K, Ho D, Wong T, Kwek K, Doshi-Velez F, Lucey C, Coffman T, Ting D. Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers. Cell Reports Medicine 2023;4(10):101230 View
  2. Thirunavukarasu A, Elangovan K, Gutierrez L, Hassan R, Li Y, Tan T, Cheng H, Teo Z, Lim G, Ting D. Clinical performance of automated machine learning: A systematic review. Annals of the Academy of Medicine, Singapore 2024;53(3):187 View
  3. Litvin A, Stoma I, Sharshakova T, Rumovskaya S, Kyovalev A. New possibilities of artificial intelligence in medicine: a narrative review. Health and Ecology Issues 2024;21(1):7 View
  4. Thirunavukarasu A, Elangovan K, Gutierrez L, Hassan R, Li Y, Tan T, Cheng H, Teo Z, Lim G, Ting D. Clinical performance of automated machine learning: A systematic review. Annals of the Academy of Medicine, Singapore 2024;53(3 - Correct DOI):187 View
  5. Shin D, Choi H, Kim D, Park J, Yoo T, Koh K. Code-Free Machine Learning Approach for EVO-ICL Vault Prediction: A Retrospective Two-Center Study. Translational Vision Science & Technology 2024;13(4):4 View
  6. Florentino B, Parmezan Bonidia R, Sanches N, da Rocha U, de Carvalho A. BioPrediction-RPI: Democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning. Computational and Structural Biotechnology Journal 2024;23:2267 View
  7. Wong C, Liu T, Wong T, Tong J, Lau H, Keane P. Development and validation of an automated machine learning model for the multi-class classification of diabetic retinopathy, central retinal vein occlusion and branch retinal vein occlusion based on color fundus photographs. JFO Open Ophthalmology 2024;7:100117 View
  8. Sabrigiriraj M, Manoharan K. Teaching Machine Learning and Deep Learning Introduction: An Innovative Tutorial-Based Practical Approach. WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION 2024;21:54 View
  9. Adigun G, Ajani Y, Enakrire R. The Intelligent Libraries: Innovation for a Sustainable Knowledge System in the Fifth (5th) Industrial Revolution. Libri 2024;74(3):211 View
  10. Heinke A, Radgoudarzi N, Huang B, Baxter S. A review of ophthalmology education in the era of generative artificial intelligence. Asia-Pacific Journal of Ophthalmology 2024;13(4):100089 View
  11. Seas A, Zachem T, Valan B, Goertz C, Nischal S, Chen S, Sykes D, Tabarestani T, Wissel B, Blackwood E, Holland C, Gottfried O, Shaffrey C, Abd-El-Barr M. Machine Learning in the Diagnosis, Management, and Care of Patients with Low Back Pain: A Scoping Review of the Literature and Future Directions. The Spine Journal 2024 View
  12. Cifuentes-González C, Rojas-Carabali W, Mejía-Salgado G, Flórez-Esparza G, Gutiérrez-Sinisterra L, Perdomo O, Gómez-Marín J, Agrawal R, de-la-Torre A. Is Automated Machine Learning useful for ocular toxoplasmosis identification and classification of the inflammatory activity?. AJO International 2024;1(4):100079 View
  13. Khan K, Zameer F, Jain P, KR R, Niranjan V, S M, H R, Padyana S. Artificial Intelligence in Revolutionizing Kidney Care and Beyond: Kid-AI Revolution. Journal of Bio-X Research 2024;7 View
  14. Hasan R, Dattana V, Mahmood S, Hussain S. Towards Transparent Diabetes Prediction: Combining AutoML and Explainable AI for Improved Clinical Insights. Information 2024;16(1):7 View
  15. Mustafa A, Naseem U, Rahimi Azghadi M. Large language models vs human for classifying clinical documents. International Journal of Medical Informatics 2025;195:105800 View
  16. Temimi A, Rebai R, Aldamen H, Souki K, Amiri K. Education at a crossroads: will AI fix learning or break it?. Management & Sustainability: An Arab Review 2025:1 View
  17. Tran H, Thu A, Twayana A, Fuertes A, Gonzalez M, Basta M, James M, Mehta K, Elias D, Figaro Y, Islek D, Frishman W, Aronow W. AI-Driven Multimodality Fusion in Cardiac Imaging: Integrating CT, MRI, and Echocardiography for Precision. Cardiology in Review 2025 View
  18. Teo Z, Thirunavukarasu A, Elangovan K, Cheng H, Moova P, Soetikno B, Nielsen C, Pollreisz A, Ting D, Morris R, Shah N, Langlotz C, Ting D. Generative artificial intelligence in medicine. Nature Medicine 2025 View
  19. Ramchandani R, Guo E, Biglou S, Sabbah S, Mostowy M, Mahiny D, Hurtubise C, Anicho-Okereke G, Shorr R, Caulley L, Propst E, Wolter N, Wasserman J, Eskander A, Siu J. Representation and Bias in Artificial Intelligence Models for Thyroid Cancer: A Systematic Review. Thyroid® 2025 View

Books/Policy Documents

  1. Reddy M, Sagar Y, Jyothi N, Rao A, Shilpa S, Velivela A. Cybernetics, Human Cognition, and Machine Learning in Communicative Applications. View
  2. Pandey N, Shabnam M, Verma S, Khan M, Verma A, Parveen S. AI-Driven Breakthroughs in Antimicrobial Resistance. View

Conference Proceedings

  1. Florentino B, Bonidia R, Carvalho A. Anais Estendidos do XXIV Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2024). Breaking Barriers: Democratizing Machine Learning for RNA-Protein Interaction Prediction in Life Sciences View
  2. Mimenbayeva A, Aruova A, Bekmagambetova G, Niyazova R, Turebayeva R, Naizagarayeva A, Tursumbayeva A. Proceedings of the 2024 8th International Conference on Advances in Artificial Intelligence. Clustering based Medical Image Segmentation: A Study on MRI Scans of Brain Tumors View
  3. Pantin R, Yunusova R, Abdullaeva B, Yuldasheva S. 2025 International Conference on Smart Learning Courses (SCME). AI Integration with Digital Infrastructure: Advancing Governance, Efficiency, and Inclusivity View
  4. Manga I. 2025 3rd International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). AutoML for All: Democratizing Machine Learning Model Building with Minimal Code Interfaces View