Tencent has developed an AI-aided diagnosis that can identify people with Parkinson’s diseases in three minutes.
Tencent Medial Lab recently demonstrated a computer-aided diagnosis Saturday at Chinese Association of Rehabilitation Medicine’s meeting on Parkinson diseases. The technique is called Smart Assessment System of the Motion Capability of Parkinson Diseases. This technique allows doctors to identify the disease based on videos of patients and patients won’t need any wearable equipment.
The traditional method to diagnose Parkinson’s diseases is to assess the patients based on the Unified Parkinson’s Disease Rating Scale (UPDRS). Doctors score specific movements of the patients face to face. On average, it usually takes more than 30 minutes to complete an assessment and since the assessment largely depends on the patients’ own description and the doctors’ visual observation, errors are likely to happen.
With the aid of AI, doctors only need video clips of the patient, which can be shot even through average smartphone cameras, and the assessment can be done within three minutes.
Wang Jian, chief physician at Huashan Hospital, said at the meeting that the results of the computer-aided diagnosis are line with the experts’ expectation and the technique is being prepared for clinical trials in larger scales.
Tencent Miying is the company’s first AI-powered medial product. The product focuses on AI-aided medial imaging and AI-aided diagnosis. According to Tencent, by July 2017, Miying has helped doctors read more than 100 million medical images and partnered with more than 100 hospitals in the country.
According to research, China has more than 3 million patients diagnosed with Parkinson’s diseases. The rate of newly diagnosed Parkinson’s disease increases with age. In China, 1% of the population aged over 55 are diagnosed with the disease and 1.7% of the population aged over 65 are diagnosed. As Chinese society continues to age, more accurate and efficient diagnose of the disease can relief patients’ pain and save resources of the medical system.