Landmark Wearable Device Trial Aims to Predict Post-Treatment Complications Using Machine Learning — What Clinicians Need to Know

References

1. 1.Massachusetts General Hospital. (2024). The Role of Wearable Devices in Predicting and Detecting Complications and Adverse Events. ClinicalTrials.gov. NCT04824066. https://clinicaltrials.gov/study/NCT04824066
2. 2.Pevnick, J. M., Birkeland, K., Zimmer, R., Elad, Y., & Kedan, I. (2018). Wearable technology for cardiology: An update and framework for the future. Trends in Cardiovascular Medicine, 28(2), 144-150. https://doi.org/10.1016/j.tcm.2017.08.003
3. 3.Berríos-Torres, S. I., Umscheid, C. A., Bratzler, D. W., Leas, B., Stone, E. C., Kelz, R. R., ... & Healthcare Infection Control Practices Advisory Committee. (2017). Centers for Disease Control and Prevention Guideline for the Prevention of Surgical Site Infection, 2017. JAMA Surgery, 152(8), 784-791. https://doi.org/10.1001/jamasurg.2017.0904
4. 4.Jencks, S. F., Williams, M. V., & Coleman, E. A. (2009). Rehospitalizations among patients in the Medicare fee-for-service program. New England Journal of Medicine, 360(14), 1418-1428. https://doi.org/10.1056/NEJMsa0803563
5. 5.Dunn, J., Runge, R., & Snyder, M. (2018). Wearables and the medical revolution. Personalized Medicine, 15(5), 429-448. https://doi.org/10.2217/pme-2018-0044
6. 6.Golinelli, D., Boetto, E., Carullo, G., Nuzzolese, A. G., Landini, M. P., & Fantini, M. P. (2020). Adoption of digital technologies in health care during the COVID-19 pandemic: Systematic review of early scientific literature. Journal of Medical Internet Research, 22(11), e22280. https://doi.org/10.2196/22280