Martin Zilic
Biographic Data
| ID | 8266118 |
|---|---|
| NAME | Martin Zilic |
| GIVEN NAMES | Martin |
| FAMILY NAME | Zilic |
| SIGNATURE | ŽILIĆ M |
| AFFILIATIONS | University of Concepción |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 1 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
An Approach to Early Detection of Metabolic Syndrome through Non-Invasive Methods in Obese Children
Early detection of MetS is possible through non-invasive methods in overweight and obese children. Two models (Clinical decision trees) based on anthropometric (non-invasive) variables with acceptable validity indexes have been presented. Clinical decision trees can be applied in different clinical and non-clinical settings, adapting to the tools available, being an economical and easy to measurement option. These methods reduce the use of blood …
No prominent works on this page.
An Approach to Early Detection of Metabolic Syndrome through Non-Invasive Methods in Obese Children
Early detection of MetS is possible through non-invasive methods in overweight and obese children. Two models (Clinical decision trees) based on anthropometric (non-invasive) variables with acceptable validity indexes have been presented. Clinical decision trees can be applied in different clinical and non-clinical settings, adapting to the tools available, being an economical and easy to measurement option. These methods reduce the use of blood …
Anthropometry (1 work) · Body mass index (1 work) · Computer Science (1 work) · Decision tree (1 work) · Diabetes, Cardiovascular Risks, and Lipoproteins (1 work) · Internal Medicine (1 work) · Logistic regression (1 work) · Machine learning (1 work) · Medicine (1 work) · Metabolic syndrome (1 work)