L2M - NSERC Development of a tool for diagnosis of diabetic complications

这里的研究人员建议开发一种软件应用程序，可以利用人工智能和机器学习，通过输入的生物标志物水平来诊断疾病。该软件应用程序将首先针对导致糖尿病失明的疾病（也称为糖尿病视网膜病变（DR））进行定制。Chakrabarti博士和他的团队在worlddiscoveries的帮助下，已经申请了PCT阶段的专利（PCT/CA2021/050924）。目前的技术使用一组基因的表达水平来诊断患者是否患有DR以及他们处于什么阶段。患者差异是存在的，该团队目前正在对500名额外的患者进行测试，以验证生物标志物技术（专利申请）。这项研究的数据将被输入到已计划开发的当前软件应用程序中。这将使家庭医生和眼科医生能够更准确地将实验室测试的数据输入该系统，以准确地诊断疾病的进展。此外，该应用程序还将用于其他依赖生物标志物水平的疾病诊断。目前的软件应用算法将针对特定疾病进行定制。目标是与生物标志物测试小组和中心合作，将现有软件集成到他们的工作流程中。目前的技术作为一种软件应用程序，将首次用于快速发展的使用生物标志物来识别和验证疾病的领域。

The researchers here propose developing a software application that can leverage artificial intelligence and machine learning to diagnose a disease using inputted biomarker levels. The software application would first be customized for disease causing blindness in diabetes, also known as diabetic retinopathy (DR). Dr. Chakrabarti and his team, with the assistance of WORLDiscoveries, have filed for a patent currently at the PCT stage (PCT/CA2021/050924). The current technology uses expression levels of a set of genes to diagnose if the patient has developed DR and what stage they are at. Patient differences exist, and the team is currently testing 500 additional patients to validate the biomarker technology (patent application filed). The data from this study will be fed into the current software application that has been planned to be developed. This will allow with much accuracy, family physicians and ophthalmologists to enter the data from the laboratory test into this system to accurately diagnose the progression of the disease.Furthermore, the application will also be developed for other disease diagnoses that are biomarker level dependent. The current software application algorithm will be tailored to disease-specific use. The goal will be to partner with biomarker testing panels and centres to integrate the existing software into their workflow. The current technology as a software application would the first of its kind to be used in the rapidly growing field of using biomarkers to identify and validate diseases.