Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics

Flavio Palmieri, Nidà Farooq Akhtar, Adriana Pané, Amanda Jiménez, Romina Paula Olbeyra, Judith Viaplana, Josep Vidal, Ana de Hollanda, Pau Gama-Perez, Josep C. Jiménez-Chillarón, Pablo M. Garcia-Roves

Open source

DOI
10.1038/s41598-024-68269-y
Published
2024-07-27
Container
Scientific Reports
Publisher
Springer Science and Business Media LLC
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1038/s41598-024-68269-y,
  title = {Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics},
  author = {Flavio Palmieri and Nidà Farooq Akhtar and Adriana Pané and Amanda Jiménez and Romina Paula Olbeyra and Judith Viaplana and Josep Vidal and Ana de Hollanda and Pau Gama-Perez and Josep C. Jiménez-Chillarón and Pablo M. Garcia-Roves},
  year = {2024},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-024-68269-y},
  url = {https://doi.org/10.1038/s41598-024-68269-y}
}

RIS

TY  - JOUR
TI  - Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics
AU  - Flavio Palmieri
AU  - Nidà Farooq Akhtar
AU  - Adriana Pané
AU  - Amanda Jiménez
AU  - Romina Paula Olbeyra
AU  - Judith Viaplana
AU  - Josep Vidal
AU  - Ana de Hollanda
AU  - Pau Gama-Perez
AU  - Josep C. Jiménez-Chillarón
AU  - Pablo M. Garcia-Roves
PY  - 2024
JO  - Scientific Reports
DO  - 10.1038/s41598-024-68269-y
UR  - https://doi.org/10.1038/s41598-024-68269-y
ER  - 

APA

Palmieri, F., Akhtar, N. F., Pané, A., Jiménez, A., Olbeyra, R. P., Viaplana, J., Vidal, J., Hollanda, A. D., Gama-Perez, P., Jiménez-Chillarón, J. C., & Garcia-Roves, P. M. (2024). Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics. Scientific Reports. https://doi.org/10.1038/s41598-024-68269-y

Source records