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https://www.selleckchem.com/products/e1210.html Patients with esophageal cancer often experience clinically relevant deterioration of quality of life (QOL) after esophagectomy owing to malnutrition, lack of physical exercise, and psychological symptoms. This study aimed to evaluate the feasibility, safety, and efficacy of a comprehensive intervention model using a mobile health system (CIMmH) in patients with esophageal cancer after esophagectomy. Twenty patients with esophageal cancer undergoing the modified McKeown surgical procedure were invited to join the CIMmH program with both online and offline components for 12 weeks. The participants were assessed before surgery and again at 1 and 3 months after esophagectomy. QOL, depressive symptoms, anxiety, stress, nutrition, and physical fitness were measured. Of the 20 patients, 16 (80%) completed the program. One month after esophagectomy, patients showed significant deterioration in overall QOL (P=.02), eating (P=.005), reflux (P=.04), and trouble with talking (P<.001). At the 3-month follow-upina. Chinese Clinical Trial Registry (ChiCTR-IPR-1800019900); http//www.chictr.org.cn/showprojen.aspx?proj=32811. Chinese Clinical Trial Registry (ChiCTR-IPR-1800019900); http//www.chictr.org.cn/showprojen.aspx?proj=32811. Performing physiotherapy exercises in front of a physiotherapist yields qualitative assessment notes and immediate feedback. However, practicing the exercises at home lacks feedback on how well patients are performing the prescribed tasks. The absence of proper feedback might result in patients performing the exercises incorrectly, which could worsen their condition. We present an approach to generate performance scores to enable tracking the progress by both the patient at home and the physiotherapist in the clinic. This study aims to propose the use of 2 machine learning algorithms, dynamic time warping (DTW) and hidden Markov model (HMM), to quantitatively assess the patient's performance with respect to

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