Integrating Machine Learning and Pathway Analysis for Precision Medicine in Type 2 Diabetes: Predictive Modeling and Therapeutic Target Identification
The global burden of Type II diabetes demands innovative strategies that combine predictive tools with targeted therapies. This study applies machine learning to the PIMA Indian dataset, identifying glucose, BMI, and age as key predictors, and integrates these with biological pathway mapping to sup...
Saved in:
| Main Authors: | Iram Wajahat, Fazel Keshtkar, Syed Ahmad Chan Bukhari |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2025-05-01
|
| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/138766 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Sociotechnical Framework for Semantic Biomedical Content Authoring and Publishing
by: Steve Fonin Mbouadeu, et al.
Published: (2022-05-01) -
Promoting Transparency and Trust in Biomedical Data: A FAIR Approach to Content Creation and Sharing
by: Asim Abbas, et al.
Published: (2024-05-01) -
The Semantics and Collocations Relation in Food Reviews
by: Fazel Keshtkar, et al.
Published: (2021-04-01) -
New discoveries in therapeutic targets and drug development pathways for type 2 diabetes mellitus under the guidance of precision medicine
by: Xinyi Tian, et al.
Published: (2025-06-01) -
AI Tutor: Student's Perceptions and Expectations of AI-Driven Tutoring Systems: A Survey-Based Investigation
by: Fazel Keshtkar, et al.
Published: (2024-05-01)