Machine Learning in Surgery

Machine learning in surgery is the use of algorithms and artificial intelligence techniques such as deep learning, data mining, and computer vision to help surgeons make decisions and improve patient outcomes. The technology has the potential to reduce human error, improve accuracy, and ultimately save lives. It is being used in areas such as robotic-assisted surgery, image processing, automatic detection of cancerous tissues in the body, and many other procedures. Machine learning has already been demonstrated to be capable of dramatically improving the accuracy of surgery, reducing the amount of time required for certain procedures, and even allowing for remote surgery to be performed from a distance. Machine learning is an important tool in providing doctors and surgeons with the best available information to make the best decisions for their patients.

← Journal of Applied Robotics and Artificial Intelligence

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30 article(s) found

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Effect of a Waterproof Device in the Noninvasive Ventilation Circuit on patient-machine Synchronization

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Nutritional Deficiencies in Pregnancy after Surgery for Morbid Obesity

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Statistical Analysis on the Influence of Flipped Classroom Teaching on Students’ Learning Effect During the Coronavirus Disease 2019 Epidemic

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Changes in Orthopedic Surgery at the Community Level

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Critical Review of Teaching and Learning Methodologies for Learners with Special Educational Needs in the 21st Century and Beyond

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Inferior Turbinate Surgery: Difficulties Between the Decision-Making and the Selection of Proper Technique

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Cosmic Surgery: Development of a New Non-Invasive Technique in Modern Surgery.

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ANH in Complex Cardiac Surgery: A Prospective Randomized Study

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Retraction Note: Leap into Fetal Surgery; In Utero Placental Mesenchymal Stem Cell Therapy, A Contemporary Approach to Treating Myelomeningocele

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