Published on in Vol 3 (2024)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/55820, first published
.

Journals
- Chisini L, Araújo C, Delpino F, Figueiredo L, Filho A, Schuch H, Nunes B, Demarco F. Dental services use prediction among adults in Southern Brazil: A gender and racial fairness-oriented machine learning approach. Journal of Dentistry 2025;161:105929 View
- Feng C, Deng F, Disis M, Gao N, Zhang L. Towards machine learning fairness in classifying multicategory causes of deaths in colorectal or lung cancer patients. Briefings in Bioinformatics 2025;26(4) View
- Allen A, Linde-Krieger L, Deschenes J, Mallahan S, Harris A, Felix M, Chalke A, Anderson A, Sharma P, King K, Grant M, Baurley J, Rankin L, Tecot S. Compliance and Satisfaction With a Protocol for Identifying Novel Targets to Support Postpartum Opioid Use Disorder Recovery: Prospective Cohort Study. JMIR Formative Research 2025;9:e77899 View
- Sánchez-Marqués R, García V, Sánchez J. Addressing the balance between fairness and performance in glioma grade prediction using bias mitigation techniques. Scientific Reports 2026;16(1) View
- Chisini L, Salvi L, Costa F, Mendes F, Pinto L, Cenci M, Pereira-Cenci T, Demarco F. Machine Learning Models for Identifying Dental Pain in Adolescents. International Dental Journal 2026;76(3):109469 View
- Ruback L, Fortunato R, Renso C, Duarte L, Teles A. Bias Mitigation in Machine Learning Models Trained on Structured Health Data: A Systematic Review. IEEE Access 2026;14:46331 View
- Saha C, Guzman A, Li Y, Gu C, Ward E, Bhat V, Hayward J, Weleff J, Ghosh S, Greiner R, Greenshaw A, Liu Y, Cao B. Common Challenges in Predicting Opioid-related Outcomes Using Machine Learning. Substance Use & Addiction Journal 2026 View
Books/Policy Documents
- Kumar A, Mohapatra H, Mishra S. Transforming the Service Sector With New Technology. View
Conference Proceedings
- Endla P, Patel R, M J, V G, J J, D G. 2025 5th International Conference on Expert Clouds and Applications (ICOECA). Robust Methodology Design to Predict Opioid Overdose System based on AI Assisted Deep Learning Principles View
