AI-based Screening for Breast Cancer Treatment

基于人工智能的乳腺癌治疗筛查

• 批准号: 558274-2020
• 负责人: Ray, Nilanjan
• 金额: $ 2.33万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=706722
• 关键词: AI; based; Screening; Breast; Cancer

AI-based Screening for Breast Cancer Treatment Breast cancer is the commonest cancer affecting women. For Canada in 2014, an estimated number of 24,400 new diagnoses of breast cancer with a reported range cost of 309-454 million CAD for diagnosis and treatment. Recently, personalized medicine has increased this cost further. The goal of the proposed research is to find AI-based solutions to replace expensive molecular tests and to reduce the significant turn around time (TAT) inherent to the complexity of these molecular assays. For this project, Alberta Health Services (AHS) and DynaLIFE Medical Labs Edmonton are partnering with Dr. Nilanjan Ray and his team at Computing Science, University of Alberta. Canadian overall healthcare quality ranking is still among the best in the world and beats the U.S. healthcare system, even though it represents 10.3% of gross domestic product (GDP) compared to 17.8% of the U.S. GDP. It is budgetarily challenging to maintain this rank. Medicine is permanently evolving, and a new paradigm includes the capacity to exploit a large amount of data through Artificial Intelligence (AI) and Machine Learning (ML) to better screen, diagnose, predict, treat and follow-up diseases. These tools can reduce costs significantly. It might be therefore critical for Canada to not only be ready to adopt these tools but to develop them. Canada has centres of excellence in the field of ML. This project is an example where these two aforementioned goals are met: 1) optimization (reduction of cost, improved TAT) of important cancer biomarkers, and 2) strengthening local ML expertise (Research, student recruitment, potential startup, and improving local economy).

基于AI的乳腺癌筛查治疗 乳腺癌是影响妇女的最常见癌症。在加拿大，2014年估计有24，400例新的乳腺癌诊断，报告的诊断和治疗费用范围为3.09 - 4.54亿加元。最近，个性化医疗进一步增加了这一成本。这项研究的目标是找到基于人工智能的解决方案，以取代昂贵的分子检测，并减少这些分子检测复杂性所固有的显著周转时间（达特）。为了这个项目，阿尔伯塔卫生服务（AHS）和埃德蒙顿DynaLIFE医疗实验室与阿尔伯塔大学计算科学的Nilanjan Ray博士和他的团队合作。 加拿大的整体医疗质量排名仍然是世界上最好的之一，击败了美国的医疗保健系统，尽管它占国内生产总值（GDP）的10.3%，而美国GDP的17.8%。保持这一排名是非常具有挑战性的。医学正在不断发展，新的范式包括通过人工智能（AI）和机器学习（ML）利用大量数据的能力，以更好地筛选，诊断，预测，治疗和随访疾病。这些工具可以大大降低成本。因此，加拿大不仅要准备采用这些工具，而且要发展这些工具。加拿大在洗钱领域设有英才中心。该项目是实现上述两个目标的一个例子：1）优化（降低成本，改善达特）重要的癌症生物标志物，2）加强本地ML专业知识（研究，学生招聘，潜在的启动和改善当地经济）。