ORIGINAL RESEARCH
Published on 28 Feb 2025
Development and validation of a prediction model for VTE risk in gastric and esophageal cancer patients
doi 10.3389/fphar.2025.1448879
- 1,470 views
- Frontiers in Pharmacology
- Experimental Pharmacology and Drug Discovery
- Research Topics
- Machine Learning and Pharmacotherapy
Machine Learning and Pharmacotherapy
7,498
Total downloads
27k
Total views and downloads
Articles
ORIGINAL RESEARCH
Published on 29 Jul 2024
Machine learning-based prediction model for the efficacy and safety of statins
doi 10.3389/fphar.2024.1334929
- 2,741 views
- 2 citations
ORIGINAL RESEARCH
Published on 08 Apr 2024
Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning
doi 10.3389/fphar.2024.1359832
- 2,291 views
- 3 citations
ORIGINAL RESEARCH
Published on 06 Mar 2024
Machine learning-based prediction of sertraline concentration in patients with depression through therapeutic drug monitoring
doi 10.3389/fphar.2024.1289673
- 2,466 views
- 7 citations
ORIGINAL RESEARCH
Published on 10 Jan 2024
Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients
doi 10.3389/fphar.2023.1334439
- 3,278 views
- 8 citations
ORIGINAL RESEARCH
Published on 05 Jan 2024
A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning
doi 10.3389/fphar.2023.1259596
- 2,745 views
- 3 citations
ORIGINAL RESEARCH
Published on 14 Sep 2023
The effect of Shengmai injection in patients with coronary heart disease in real world and its personalized medicine research using machine learning techniques
doi 10.3389/fphar.2023.1208621
- 1,796 views
- 4 citations
ORIGINAL RESEARCH
Published on 30 Jun 2023
Development and economic assessment of machine learning models to predict glycosylated hemoglobin in type 2 diabetes
doi 10.3389/fphar.2023.1216182
- 2,556 views
- 6 citations
