Improving Pain Management in Patients with Sickle Cell Disease Using Machine Learning Techniques
Year: 2020
Type: article
Abstract: Sickle cell disease (SCD) is an inherited red blood cell disorder that can cause a multitude of complications throughout a patient's life.Pain is the most common complication and a significant cause of morbidity.Since pain is a highly subjective experience, both medical providers and patients express difficulty in determining ideal treatment and management strategies for pain.Therefore, the development of objective pain assessment and pain forecasting methods is critical to pain management in SCD.On the other hand, the rapidly increasing use of mobile health (mHealth) technology and wearable devices gives the ability to build a remote health intervention system for SCD.Hence, the objective of this study is to leverage machine learning techniques, mHealth, and wearable devices together to improve pain management in SCD in both clinical and remote environments.I want to express my profound appreciation to all those who have helped me during my doctoral journey.First and foremost, I would like to express my special gratitude and thanks to my advisor Dr. Tanvi Banerjee.She has been there to provide her genuine support and guidance at all times and helped me grow as a research scientist.I would also like to thank my committee members, Dr. Krishnaprasad Thirunarayan, Dr. Michael Raymer, and Dr. Nirmish Shah, for their thoughtful comments and patience.I especially want to
Author: Fan Yang
Language: English
Subfield: Genetics (clinical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W3164291498