AI Medical Compendium Topic

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Outcome Assessment, Health Care

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Volume-outcome relationship in intra-abdominal robotic-assisted surgery: a systematic review.

Journal of robotic surgery
As robotic-assisted surgery (RAS) expands to smaller centres, platforms are shared between specialities. Healthcare providers must consider case volume and mix required to maintain quality and cost-effectiveness. This can be informed, in-part, by the...

Effects of Upper Limb Robot-Assisted Rehabilitation Compared with Conventional Therapy in Patients with Stroke: Preliminary Results on a Daily Task Assessed Using Motion Analysis.

Sensors (Basel, Switzerland)
Robotic rehabilitation of the upper limb has demonstrated promising results in terms of the improvement of arm function in post-stroke patients. The current literature suggests that robot-assisted therapy (RAT) is comparable to traditional approaches...

A machine learning analysis to evaluate the outcome measures in inflammatory myopathies.

Autoimmunity reviews
OBJECTIVE: To assess the long-term outcome in patients with Idiopathic Inflammatory Myopathies (IIM), focusing on damage and activity disease indexes using artificial intelligence (AI).

Leveraging Data and Technology to Enhance Interdisciplinary Collaboration and Health Outcomes.

Yearbook of medical informatics
OBJECTIVE: To give an overview of recent research and propose a selection of best papers published in 2022 in Informatics for One Health.

Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment.

European radiology
OBJECTIVES: To evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in comparison to the Eastern Cooperative Oncology Group (ECOG) score for survival of patients with advanced pancreatic cancer treated with high-intensity ...

Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model.

BMC research notes
OBJECTIVE: This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya.

Predicting treatment response using machine learning: A registered report.

The British journal of clinical psychology
OBJECTIVE: Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively scr...

Predicting Outcomes of Antidepressant Treatment in Community Practice Settings.

Psychiatric services (Washington, D.C.)
OBJECTIVE: The authors examined whether machine-learning models could be used to analyze data from electronic health records (EHRs) to predict patients' responses to antidepressant medications.

Seeing the whole elephant: integrated advanced data analytics in support of RWE for the development and use of innovative pharmaceuticals.

Expert review of pharmacoeconomics & outcomes research
INTRODUCTION: The 21 century has brought about significant technological advancement, allowing the collection of new types of data from the real world on an unprecedented scale. The healthcare industry will benefit immensely from this abundance of pa...