AIMC Topic: Patient Compliance
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How to Improve Compliance with Protective Health Measures during the COVID-19 Outbreak: Testing a Moderated Mediation Model and Machine Learning Algorithms.
International journal of environmental research and public health
Oct 4, 2020
In the wake of the sudden spread of COVID-19, a large amount of the Italian population practiced incongruous behaviors with the protective health measures. The present study aimed at examining psychological and psychosocial variables that could predi...
Improved patient satisfaction and diagnostic accuracy in skin diseases with a Visual Clinical Decision Support System-A feasibility study with general practitioners.
PloS one
Jul 29, 2020
Patient satisfaction is an important indicator of health care quality, and it remains an important goal for optimal treatment outcomes to reduce the level of misdiagnoses and inappropriate or absent therapeutic actions. Digital support tools for diff...
Applying machine learning to predict future adherence to physical activity programs.
BMC medical informatics and decision making
Aug 22, 2019
BACKGROUND: Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured...
Artificial Intelligence in Health: New Opportunities, Challenges, and Practical Implications.
Yearbook of medical informatics
Aug 16, 2019
OBJECTIVES: To summarise the state of the art during the year 2018 in consumer health informatics and education, with a special emphasis on the special topic of the International Medical Informatics Association (IMIA) Yearbook for 2019: "Artificial i...
Artificial Intelligence for Clinical Trial Design.
Trends in pharmacological sciences
Jul 17, 2019
Clinical trials consume the latter half of the 10 to 15 year, 1.5-2.0 billion USD, development cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the investment into the trial itself but also the preclinical developm...
Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.
Journal of clinical monitoring and computing
Sep 24, 2018
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...
Ketorolac
Humans
Treatment Outcome
Infusions, Intravenous
Data Interpretation, Statistical
Signal Processing, Computer-Assisted
Patient Readmission
Medical Informatics
Colorectal Surgery
Colonic Neoplasms
Patient Compliance
Inflammatory Bowel Diseases
Reproducibility of Results
Pilot Projects
Monitoring, Intraoperative
Artificial Intelligence
Machine Learning
Software
Algorithms
Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy.
BMC medical informatics and decision making
Sep 18, 2018
BACKGROUND: Patients suffering obstructive sleep apnea are mainly treated with continuous positive airway pressure (CPAP). Although it is a highly effective treatment, compliance with this therapy is problematic to achieve with serious consequences f...
Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.
Physiological measurement
Jul 23, 2018
OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupe...
Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme.
Computer methods and programs in biomedicine
May 29, 2018
BACKGROUND: In the time since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in the formulation of an effective and efficient strategy to improve the participation rate has been growing. The aim ...
Application of Machine Learning to Predict Dietary Lapses During Weight Loss.
Journal of diabetes science and technology
May 24, 2018
BACKGROUND: Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of resea...
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