A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome.

Wang DD, Li YF, Mao YZ, He SM, Zhu P, Wei QL

DOI: 10.3389/fnut.2022.851275
Published: 2022
Container: Frontiers in nutrition
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fnut.2022.851275,
  title = {A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome.},
  author = {Wang DD and Li YF and Mao YZ and He SM and Zhu P and Wei QL},
  year = {2022},
  journal = {Frontiers in nutrition},
  doi = {10.3389/fnut.2022.851275},
  url = {https://doi.org/10.3389/fnut.2022.851275}
}

RIS

TY  - JOUR
TI  - A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome.
AU  - Wang DD
AU  - Li YF
AU  - Mao YZ
AU  - He SM
AU  - Zhu P
AU  - Wei QL
PY  - 2022
JO  - Frontiers in nutrition
DO  - 10.3389/fnut.2022.851275
UR  - https://doi.org/10.3389/fnut.2022.851275
ER  -

APA

DD, W., YF, L., YZ, M., SM, H., P, Z., & QL, W. (2022). A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome.. Frontiers in nutrition. https://doi.org/10.3389/fnut.2022.851275

Source records

pubmed · retrieved 2026-09-26T19:55:15.659Z