AI-Assisted Diagnosis Application for Primary Care Outpatients




To reduce waiting time and improve diagnosis, this mobile application allows outpatients to go through an additional virtual examination in the waiting room after their physical pre-consultation screening. In this virtual examination, the outpatient will go through a skin scan and report their symptoms in the application which is deployed on their personal device. After the virtual screening, a consolidated report will be generated. This report will then be presented to the doctor by the patient during the consultation. The report will contain relevant information about the patient such as their family history, results of the skin check and suggested ailment. The technology can support the doctor, in reducing the number of basic questions asked at the start of every consultation. This will save both parties' time and facilitate a more in-depth checkup. By reducing wait time, the application also reduces the infrastructure stress generated by waiting outpatients, hence reducing infrastructure maintenance costs. The application is designed to be used in the pre-consultation screening procedure conducted in hospitals and polyclinics. The nominal fee for the application is paid by the outpatient. No personally identifiable data will be collected by the application. Immediate needs of the tech owner will be to seek collaboration opportunities with clinical partners, so as to bring the technology into a pilot launch.


Currently, we offer 29 identifiable conditions and 380 possible reports. For the skin check, we are currently utilising 10 open sourced skin datasets. The application also has multilingual capabilities. This application makes use of a supervised learning algorithm to provide the messaging features. To provide the skin check feature, the application utilises neural networks to train the model. The AI agents trained are combined in a dynamic proprietary system to form the mobile application.


This application is designed to be deployed in a hospital or polyclinic setting to improve the pre-consultation screening procedure when partnered with a clinical partner. A customised version of the application can also be deployed in specialist clinics. The technology can also be used for customer engagement to personalise recommendations for skincare products if partnered with a cosmetic company and provided with a database of facial images. Another application of the technology would be usage for customer engagement in pharmacies to personalise recommendations for healthcare products if partnered with a pharmaceutical company.