Ming Mo
Biographic Data
| ID | 9923450 |
|---|---|
| NAME | Ming Mo |
| GIVEN NAMES | Ming |
| FAMILY NAME | Mo |
| SIGNATURE | MO M |
| AFFILIATIONS | Guangdong Medical College |
| ORCID | 0009-0004-5891-8815 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Systemic inflammatory indices for predicting severe placenta accreta spectrum
Background: Placenta Accreta Spectrum (PAS) disorders are associated with substantial maternal morbidity, and distinguishing mild from severe forms prenatally remains difficult. Inflammatory indices derived from peripheral blood counts have emerged as promising biomarkers, yet their role in grading PAS severity has been insufficiently investigated. This study aimed to assess the discriminative value of the systemic immune-inflammation index (SII)…
A deep hybrid learning framework with attention-enhanced feature extraction for BMI prediction based on physical fitness
Background: Body Mass Index (BMI) assessment remains a critical challenge in university health monitoring, where traditional methods fail to capture dynamic relationships between physical fitness indicators and body composition. This study develops a novel predictive framework to address this gap through advanced machine learning techniques applied to longitudinal fitness data from Chinese university students. Methods: We analyzed 6,698 male stud…
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A deep hybrid learning framework with attention-enhanced feature extraction for BMI prediction based on physical fitness
Background: Body Mass Index (BMI) assessment remains a critical challenge in university health monitoring, where traditional methods fail to capture dynamic relationships between physical fitness indicators and body composition. This study develops a novel predictive framework to address this gap through advanced machine learning techniques applied to longitudinal fitness data from Chinese university students. Methods: We analyzed 6,698 male stud…
Systemic inflammatory indices for predicting severe placenta accreta spectrum
Background: Placenta Accreta Spectrum (PAS) disorders are associated with substantial maternal morbidity, and distinguishing mild from severe forms prenatally remains difficult. Inflammatory indices derived from peripheral blood counts have emerged as promising biomarkers, yet their role in grading PAS severity has been insufficiently investigated. This study aimed to assess the discriminative value of the systemic immune-inflammation index (SII)…
Artificial Intelligence (1 work) · Body Composition Measurement Techniques (1 work) · Computer Science (1 work) · Context-Aware Activity Recognition Systems (1 work) · Feature extraction (1 work) · Inflammatory Biomarkers in Disease Prognosis (1 work) · inflammatory markers (1 work) · Machine learning (1 work) · Maternal and fetal healthcare (1 work) · Maternal morbidity (1 work)