Miye Wang
Biographic Data
| ID | 7955670 |
|---|---|
| NAME | Miye Wang |
| GIVEN NAMES | Miye |
| FAMILY NAME | Wang |
| SIGNATURE | WANG M |
| AFFILIATIONS | West China Hospital of Sichuan University |
| ORCID | 0000-0002-4137-0310 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
An Explainable AI Approach for the Rapid Diagnosis of Covid-19 Using Ensemble Learning Algorithms
Background: Artificial intelligence-based disease prediction models have a greater potential to screen COVID-19 patients than conventional methods. However, their application has been restricted because of their underlying black-box nature. Objective: To addressed this issue, an explainable artificial intelligence (XAI) approach was developed to screen patients for COVID-19. Methods: A retrospective study consisting of 1,737 participants (759 COV…
Potential Biomarkers for Predicting Depression in Diabetes Mellitus
Objective: To identify the potential biomarkers for predicting depression in diabetes mellitus using support vector machine to analyze routine biochemical tests and vital signs between two groups: subjects with both diabetes mellitus and depression, and subjects with diabetes mellitus alone. Methods: Electronic medical records upon admission and biochemical tests and vital signs of 135 patients with both diabetes mellitus and depression and 187 p…
No prominent works on this page.
Potential Biomarkers for Predicting Depression in Diabetes Mellitus
Objective: To identify the potential biomarkers for predicting depression in diabetes mellitus using support vector machine to analyze routine biochemical tests and vital signs between two groups: subjects with both diabetes mellitus and depression, and subjects with diabetes mellitus alone. Methods: Electronic medical records upon admission and biochemical tests and vital signs of 135 patients with both diabetes mellitus and depression and 187 p…
An Explainable AI Approach for the Rapid Diagnosis of Covid-19 Using Ensemble Learning Algorithms
Background: Artificial intelligence-based disease prediction models have a greater potential to screen COVID-19 patients than conventional methods. However, their application has been restricted because of their underlying black-box nature. Objective: To addressed this issue, an explainable artificial intelligence (XAI) approach was developed to screen patients for COVID-19. Methods: A retrospective study consisting of 1,737 participants (759 COV…
Internal Medicine (2 works) · Medicine (2 works) · Receiver operating characteristic (2 works) · AdaBoost (1 work) · Algorithm (1 work) · Artificial Intelligence (1 work) · Blood pressure (1 work) · Cholesterol (1 work) · Chronic Disease Management Strategies (1 work) · Computer Science (1 work)