National Taiwan University Hospital has hundreds of operations every day. After the operation, patients go home to deal with the wound, which often leads to unpredictable situations, such as poor wound care, inflammation, redness and swelling, and even purulent bleeding. However, returning to the hospital when in doubt not only wastes medical resources, but also wastes the time of doctors and patients.

In order to track the postoperative results, find the abnormal situation of the wound in time and provide suggestions in time. Taiwan Province Provincial University and National Taiwan University Hospital jointly developed the technology of "Intelligent Postoperative Wound Tracking System (AI-SWAS)", and established an artificial intelligence platform and a mobile phone APP. This is the first platform in Taiwan Province that can directly interpret wound photos through artificial intelligence, and it has two functions: telemedicine and expert consultation.

The accuracy of the platform is over 90%. AI-SWAS platform uses artificial intelligence algorithm to analyze the wound, which can detect the redness, swelling, necrosis and infection of the wound after operation. Dai Haozhi, director of plastic surgery at National Taiwan University Hospital, said that AI-SWAS has achieved 90% accuracy in the test of wound state (normal/abnormal) and 9 1% accuracy in the interpretation of wound symptoms (swelling, necrosis, bleeding and pus discharge).

Through the AI-SWAS mobile phone APP of National Taiwan University, patients can record postoperative wounds with their mobile phones at home, upload photos of postoperative wounds to the AI-SWAS platform every 2-3 days, and the platform will notify doctors to check photos through SMS, and feed back treatment suggestions to patients through the AI-SWAS APP. Patients can see photos of postoperative wounds and treatment suggestions, such as health education guidelines, on the artificial intelligence SWAS application.

According to Dai Haozhi, AI-SWAS can judge whether the wound is slowly healing and developing towards recovery from the color of the wound by automatically interpreting the wound photos. If there is inflammation, the color of the wound will change. After AI-SWAS is automatically interpreted, it can provide the second opinion of similar experts, greatly reducing the interpretation time of medical staff.

Patients can also establish communication channels with their attending physicians, so that patients can get appropriate treatment advice in time, and medical staff can also provide remote care in a more convenient way, saving patients' round-trip time and medical workload.

At present, AI-SWAS system has been used in surgical wound care in NTU hospital. Dai Haozhi said that in the coming year, NTU Hospital will also expand the mobile scope of this system from surgical wounds to various wound care.