How artificial intelligence makes diagnosis easier during Covid-19 and commuting easier - News

In Partnership With: TVB Limited- On September 18, 2020, Hong Kong TVB conducted an in-depth interview with Imsight Technology on the topic of "The development of Artificial Intelligence Medical Imaging companies in the Greater Bay area" and discussed it with the team from Hong Kong region. Mr Chapman Lee, our Director, was interviewed with topics related to the responses of company operation in the midst of the epidemic situation. Let us look at the highlights of this interview.

Mr. Chapman Lee, one of the core members of the company, mentioned that “Artificial Intelligence, this computer technology, is constantly learning, and the accuracy of the system is based on the data given to the system by the doctor and its accuracy will not decrease due to heavy workload. In addition, Artificial Intelligence can assist doctors at their work if they are suffering from immense workload, thereby increasing the efficiency and accuracy of diagnosis.”

Imsight Technology is a start-up company in Hong Kong that utilizes advanced artificial intelligence deep learning and computer medical image analysis technology, combined with high-quality medical data to develop an efficient and accurate medical image-assisted system to enhance the accuracy of clinical diagnosis.

One of the well-known products is “Cervical-Sight.” Allowing automated analysis of cervical fluid-related cytopathic images, it utilizes a deep learning technique related to convolutional neural networks with rapid screening, locating diseased cells under TBS guidelines.

Cervical cancer liquid-based cell screening is diagnosed by A.I deep learning technology

In the midst of COVID-19 pandemic, routine lung cancer screenings schedules were dragged and most healthcare resources in public sectors were allocated into identifying confirmed cases. We are providing solutions for optimizing detection of pneumonia and these sorts of features are capable of streamlining doctors’ workflow by prioritizing the cases based on the risk stratification. Referring to the users’ comments, this information computed by AI could provide an useful reference to the doctors which are handling extreme workloads daily in reading each patient file and therefore assist the process for next-step appropriate treatment.