Machine learning has the potential to be a useful method in plastic surgery.



Researchers are looking at using machine learning, a subfield of artificial intelligence, to enhance medical care and patient outcomes as the amount of electronic data generated by the healthcare system grows. An overview of machine learning and some of the ways it could contribute to advancements in plastic surgery are presented in a special topic article in the May issue of Plastic and Reconstructive Surgery.

Machine learning has the potential to be a powerful tool in plastic surgery, enabling surgeons to use complex clinical data to direct crucial clinical decisions.

In plastic surgery research and practice, machine learning shows promise. Machine learning uses historical data to build algorithms that can learn new things.

Machine learning approaches that are objective and data-driven"—especially now that the ASPS's 'Tracking Operations and Outcomes for Plastic Surgeons' (TOPS) database is accessible.

Surgery for Burns. A machine learning method for predicting burn healing time has already been developed, providing a useful tool for determining burn depth. Algorithms may also be created to estimate the percentage of body surface area burned in a timely manner, which is crucial information for patient resuscitation and surgical preparation.

Microsurgery is a form of surgery in which small incisions are Based on smartphone images, a postoperative microsurgery application has been created to track blood perfusion of tissue flaps. Algorithms can be built in the future to assist in recommending the best reconstructive surgery approach for individual patients.

Craniofacial Surgery is a form of surgery that deals with the face and jaws. Machine learning techniques have been developed for the automated diagnosis of infant skull growth defects (craniosynostosis). Identifying known and unknown genes responsible for cleft lip and palate may be aided by future algorithms.

Surgery of the Hand and Peripheral Nerves Machine learning techniques may help predict the effectiveness of tissue-engineered nerve grafts, create automated controls for hand and arm neuroprostheses in patients with severe spinal cord injuries, and improve hand surgery planning and prediction.

Aesthetic surgery is a form of cosmetic surgery. Machine learning may be used in cosmetic surgery to predict and simulate the results of aesthetic facial surgery and reconstructive breast surgery.