Cargando…
Predicting prenatal depression and assessing model bias using machine learning models
Perinatal depression (PND) is one of the most common medical complications during pregnancy and postpartum period, affecting 10–20% of pregnant individuals. Black and Latina women have higher rates of PND, yet they are less likely to be diagnosed and receive treatment. Machine learning (ML) models b...
Autores principales: | Huang, Yongchao, Alvernaz, Suzanne, Kim, Sage J., Maki, Pauline, Dai, Yang, Bernabé, Beatriz Penñalver |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371186/ https://www.ncbi.nlm.nih.gov/pubmed/37503225 http://dx.doi.org/10.1101/2023.07.17.23292587 |
Ejemplares similares
-
Statistical quantification of confounding bias in machine learning models
por: Spisak, Tamas
Publicado: (2022) -
Racial Equity in Healthcare Machine Learning: Illustrating Bias in Models With Minimal Bias Mitigation
por: Barton, Michael, et al.
Publicado: (2023) -
A machine learning model with human cognitive biases capable of learning from small and biased datasets
por: Taniguchi, Hidetaka, et al.
Publicado: (2018) -
Machine Learning-Based Predictive Modeling of Postpartum Depression
por: Shin, Dayeon, et al.
Publicado: (2020) -
Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
por: Kovács, Dávid Péter, et al.
Publicado: (2021)