A Machine Learning Pipeline to Analyze Global Sentiment and Factors Influencing Retinoblastoma Treatment Hesitancy: Observational Infodemiology Study.

Wong ES, Choy RW, Tang EW, Zhang Y, Zhang XJ, Zhou L, Chu WK, Chen LJ, Tham CC, Pang CP, Yam JC

Open source

DOI
10.2196/73364
Published
2026 Aug 11
Container
Journal of medical Internet research
Publisher
Not recorded
Open access
yes

Credibility signals

limited evidence Score 45/100 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:10.2196/73364,
  title = {A Machine Learning Pipeline to Analyze Global Sentiment and Factors Influencing Retinoblastoma Treatment Hesitancy: Observational Infodemiology Study.},
  author = {Wong ES and Choy RW and Tang EW and Zhang Y and Zhang XJ and Zhou L and Chu WK and Chen LJ and Tham CC and Pang CP and Yam JC},
  year = {2026},
  journal = {Journal of medical Internet research},
  doi = {10.2196/73364},
  url = {https://doi.org/10.2196/73364}
}

RIS

TY  - JOUR
TI  - A Machine Learning Pipeline to Analyze Global Sentiment and Factors Influencing Retinoblastoma Treatment Hesitancy: Observational Infodemiology Study.
AU  - Wong ES
AU  - Choy RW
AU  - Tang EW
AU  - Zhang Y
AU  - Zhang XJ
AU  - Zhou L
AU  - Chu WK
AU  - Chen LJ
AU  - Tham CC
AU  - Pang CP
AU  - Yam JC
PY  - 2026
JO  - Journal of medical Internet research
DO  - 10.2196/73364
UR  - https://doi.org/10.2196/73364
ER  - 

APA

ES, W., RW, C., EW, T., Y, Z., XJ, Z., L, Z., WK, C., LJ, C., CC, T., CP, P., & JC, Y. (2026). A Machine Learning Pipeline to Analyze Global Sentiment and Factors Influencing Retinoblastoma Treatment Hesitancy: Observational Infodemiology Study.. Journal of medical Internet research. https://doi.org/10.2196/73364

Source records