Improving Postoperative Outcomes in Oncology Patients with Wearable Device Data and Machine Learning

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This article is about how machine learning can be used to improve the postoperative continuous recovery scores of oncology patients in perioperative care. The article puts emphasis on the data obtained by wearables which can provide insights and serve as an efficient tool for monitoring the recovery of patients. Data gathered from wearables and subsequent analysis can be done to better access the treatment effectiveness and potential risks.

MDPI is an open access scientific publisher publishing around 4,400 journals and 31,000 articles every year and is based in Basel, Switzerland. MDPI promotes the free exchange of scientific knowledge and emphasizes the importance of a high ethical standard in scientific publishing. It produces a range of titles, from general science to specific disciplines in the physical, chemical, and biological sciences. All articles published by MDPI are open access and made available worldwide, under an open access license.

The article was written by Dr. Giulia Rognini, who is a professor and researcher in perioperative medicine in Italy and a professor at the University of Pisa Medical School. She has a vast amount of research and experience on wearables, perioperative monitoring and machine learning. Being a professor, she has experience in teaching and mentoring promising students and she works collaboratively with the industry in national and international research projects with the aim of better understanding the outcomes of oncological interventions.

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