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Orthopedic Procedures

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Performance of a NLP Tool for Text Classification from Orthopaedic Operative Reports, Using Data from the Large Network of Clinical Data Warehouses of the West of France: The HACRO-HUGORTHO Project.

Studies in health technology and informatics
Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks related to implanted materials. Due to population ageing and expanding demands, total hip, knee, and ...

Leveraging Artificial Intelligence and Digital Health to Address Health-Related Social Needs and Optimize Risk-Based Value in Orthopaedic Surgery.

Instructional course lectures
As the health care landscape evolves toward value-based care and emphasizes health-related social needs, the importance of developing health policies and digital health solutions that foster health equity and risk-based reimbursement strategies has g...

A Machine Learning Solution to Predict Elective Orthopedic Surgery Case Duration.

Studies in health technology and informatics
We used surgery durations, patient demographic and personnel data taken from the East Kent Hospitals University NHS Foundation Trust (EKHUFT) over a period of 10 years (2010-2019) for a total of 25,352 patients that underwent 15 highest volume electi...

Editorial Commentary: Machine Learning in Medicine Requires Clinician Input, Faces Barriers, and High-Quality Evidence Is Required to Demonstrate Improved Patient Outcomes.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Machine learning (ML) and artificial intelligence (AI) may be described as advanced statistical techniques using algorithms to "learn" to evaluate and predict relationships between input and results without explicit human programming, often with high...

Feed rate control in robotic bone drilling process.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The bone drilling process is characterised by various parameters, the most important of which are the feed rate (mm/s) and the drill speed (rpm). They highly reflect the final effects and results of the drilling process, such as mechanical and therma...

Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol.

Journal of orthopaedic surgery and research
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are interwoven into our everyday lives and have grown enormously in some major fields in medicine including cardiology and radiology. While these specialties have quickly embraced AI ...

Clinical predictive modelling of post-surgical recovery in individuals with cervical radiculopathy: a machine learning approach.

Scientific reports
Prognostic models play an important role in the clinical management of cervical radiculopathy (CR). No study has compared the performance of modern machine learning techniques, against more traditional stepwise regression techniques, when developing ...

The Future of Skull Base Surgery: A View Through Tinted Glasses.

World neurosurgery
In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years based on the many areas of current research in biology and technology. Many of these advances will a...