AIMC Topic: Arthralgia

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Comparison of predictive models for knee pain and analysis of individual and physical activity variables using interpretable machine learning.

The Knee
BACKGROUND: Knee pain is associated with not only individual factors such as age and obesity but also physical activity factors such as occupational activities and exercise, which has a significant impact on the lives of adults and the elderly.

Investigating artificial intelligence models for predicting joint pain from serum biochemistry.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: The study used machine learning models to predict the clinical outcome with various attributes or when the models chose features based on their algorithms.

Thrombosed Persistent Median Artery with Coexisting Bifid Median Nerve in a Robotic Arthroplasty Surgeon: A Case Report.

JBJS case connector
CASE: A 47-year-old orthopaedic surgeon presented with acute volar left wrist pain. He performed over 250 robot-assisted knee arthroplasties each year. Color Doppler evaluation revealed bilateral persistent median arteries and bifid median nerves, wi...

Gait Alterations and Association With Worsening Knee Pain and Physical Function: A Machine Learning Approach With Wearable Sensors in the Multicenter Osteoarthritis Study.

Arthritis care & research
OBJECTIVE: The objective of this study was to identify gait alterations related to worsening knee pain and worsening physical function, using machine learning approaches applied to wearable sensor-derived data from a large observational cohort.

Predicting postoperative opioid use with machine learning and insurance claims in opioid-naïve patients.

American journal of surgery
BACKGROUND: The clinical impact of postoperative opioid use requires accurate prediction strategies to identify at-risk patients. We utilize preoperative claims data to predict postoperative opioid refill and new persistent use in opioid-naïve patien...

Objective characterization of hip pain levels during walking by combining quantitative electroencephalography with machine learning.

Scientific reports
Pain is an undesirable sensory experience that can induce depression and limit individuals' activities of daily living, in turn negatively impacting the labor force. Affected people frequently feel pain during activity; however, pain is subjective an...

Assessment of knee pain from MR imaging using a convolutional Siamese network.

European radiology
OBJECTIVES: It remains difficult to characterize the source of pain in knee joints either using radiographs or magnetic resonance imaging (MRI). We sought to determine if advanced machine learning methods such as deep neural networks could distinguis...

Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection.

Radiology
Purpose To determine the feasibility of using a deep learning approach to detect cartilage lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due to cartilage degeneration, and acute cartilage injury) wit...

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm.

Cancer medicine
Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor-related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm ...