Peer-reviewedCC BYBrain and behavior
Ensemble‐Based Machine Learning Models for Classifying Intervention‐Related Psychological Outcome Patterns in Menopausal Women Treated With Pimpinella anisum
4 affiliations
- 1Westlake University
- 2Ministry of AYUSH
- 3Huazhong University of Science and Technology
- 4Westlake University, Hangzhou
Related
- The Relationship Between Menopausal Symptoms and Life Satisfaction in Menopausal Women: The Mediating Role of Psychological Flexibility
- Menopausal symptoms, sexual function, and psychological well-being in women across the menopausal transition.
- Effect of Nursing Educational Intervention Based on Self-Determination Theory on Self-Efficacy and Quality of Life among Menopausal Women
- Effects of the physical activity guidelines with or without the dietary guidelines on cardiometabolic disease risk among pre- and post-menopausal women: study protocol for the Multiple Risk Factor Intervention Trial (Ms. FIT) RCT
- An Integrated Framework for Classifying Intervention Mechanisms and Measurement Methodologies of Lower-Limb Proprioception in Patients with Stroke: A Systematic Review and Exploratory Meta-Analysis
BibTeX
@article{heyat2026ensemblebased,
title = {{Ensemble‐Based Machine Learning Models for Classifying Intervention‐Related Psychological Outcome Patterns in Menopausal Women Treated With Pimpinella anisum}},
author = {Md Belal Bin Heyat and Arshiya Sultana and Attiq Ur Rehman and Arfa Begum and Mohamad Sawan},
journal = {Brain and behavior},
year = {2026},
month = oct,
url = {https://europepmc.org/article/PMC/PMC13653034},
note = {CC BY},
}
RIS
TY - JOUR
TI - Ensemble‐Based Machine Learning Models for Classifying Intervention‐Related Psychological Outcome Patterns in Menopausal Women Treated With Pimpinella anisum
AU - Md Belal Bin Heyat
AU - Arshiya Sultana
AU - Attiq Ur Rehman
AU - Arfa Begum
AU - Mohamad Sawan
PY - 2026
DA - 2026/10/01
JO - Brain and behavior
UR - https://europepmc.org/article/PMC/PMC13653034
SN - 2162-3279
ER -