A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis

2024/08/30 by Wei A. Huang, Wei Angel Huang, Matthew Engelhard +10 · 1 voice
Computer Science · Neuroscience · #Autism Spectrum Disorder Research #Machine Learning in Healthcare #Text and Document Classification Technologies

paper · doi:10.1016/j.jbi.2024.104711

openalex publication_date 2024/08/30 · crossref created 2024/08/30 · crossref issued 2024/09/01 · crossref published 2024/09/01 · crossref published-print 2024/09/01 · openalex created_date 2025/10/10 · crossref deposited 2025/11/07 · crossref indexed 2026/07/24 · openalex updated_date 2026/08/01

Citations

• A Review on Multi-Label Learning Algorithms
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
• The Female Autism Phenotype and Camouflaging: a Narrative Review
• A Survey on Multi-Task Learning

Discussions

• Wei A. Huang, Matthew Engelhard, et al, A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis, Journal of Biomedical Informatics, Volume [bsky, 0 points, 0 comments]