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

Decision Support for Health Professionals (1147) Autism Spectrum Disorder (ASD) (98) Artificial Intelligence (1216) Machine Learning (1401) Clinical Information and Decision Making (1340) Clinical Informatics (919) Diagnostic Tools in Mental Health (224) Precision Medicine and Genetics (44)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24754, first published .
Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning

Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning

Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning

Authors of this article:

Haishuai Wang1, 2 Author Orcid Image ;   Paul Avillach1 Author Orcid Image
Article Authors Cited by (31) Tweetations (3) Metrics

Journals

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  13. Nisar S, Haris M. Neuroimaging genetics approaches to identify new biomarkers for the early diagnosis of autism spectrum disorder. Molecular Psychiatry 2023;28(12):4995 View
  14. Wang M, Richmond L, Schleider J, Nelson B, Luhmann C. Predicting internalizing symptoms with machine learning: identifying individuals that need care. Journal of American College Health 2023:1 View
  15. S R R, Mounika S. Autism Spectrum Disorder Classification Using Machine Learning and Deep Learning- A Survey. EAI Endorsed Transactions on Pervasive Health and Technology 2023;9 View
  16. Alowais S, Alghamdi S, Alsuhebany N, Alqahtani T, Alshaya A, Almohareb S, Aldairem A, Alrashed M, Bin Saleh K, Badreldin H, Al Yami M, Al Harbi S, Albekairy A. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Medical Education 2023;23(1) View
  17. Balasubramanian J, Gururaj B, Gayatri N. An effective autism spectrum disorder screening method using machine learning classification techniques. Concurrency and Computation: Practice and Experience 2024;36(2) View
  18. Sriramakrishnan G, Rani V, Thatavarti S, Maram B. Chronological pelican remora optimization-enabled deep learning for detection of autism spectrum disorder. Signal, Image and Video Processing 2024;18(1):515 View
  19. Taz T, Arslanturk S. Unveiling genetic variant-level biomarkers for aggressive prostate cancer. Informatics in Medicine Unlocked 2023;43:101410 View
  20. Barnett E, Onete D, Salekin A, Faraone S. Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2024;21(1):169 View
  21. Xu Q, Yang J, Zhang H, Jie X, Bandara D. Enhancing Few-Shot Action Recognition Using Skeleton Temporal Alignment and Adversarial Training. IEEE Access 2024;12:31745 View
  22. Bandara D, Riccardi K. Graph Node Classification to Predict Autism Risk in Genes. Genes 2024;15(4):447 View
  23. Fatima A, Masood S. Machine learning approaches for neurological disease prediction: A systematic review. Expert Systems 2024 View
  24. Xie X, Zhou R, Fang Z, Zhang Y, Wang Q, Liu X. Seeing beyond words: Visualizing autism spectrum disorder biomarker insights. Heliyon 2024;10(9):e30420 View
  25. Nussinov R, Yavuz B, Demirel H, Arici M, Jang H, Tuncbag N. Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide. Frontiers in Cell and Developmental Biology 2024;12 View

Books/Policy Documents

  1. Faria B, Ribeiro M, Simões R, Valente S, Rocha N. Information Systems and Technologies. View