AI-based Screening for Breast Cancer Treatment

基于人工智能的乳腺癌治疗筛查

基本信息

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

项目摘要

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).

基于人工智能的乳腺癌治疗筛查乳腺癌是影响女性的最常见癌症。 2014 年，加拿大估计新诊断出 24,400 例乳腺癌，据报告诊断和治疗费用为 309-4.54 亿加元。最近，个性化医疗进一步增加了这一成本。拟议研究的目标是找到基于人工智能的解决方案来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着周转时间（TAT）。对于这个项目，阿尔伯塔省卫生服务中心 (AHS) 和埃德蒙顿 DynaLIFE 医学实验室与阿尔伯塔大学计算科学部的 Nilanjan Ray 博士及其团队合作。加拿大的整体医疗保健质量排名仍然位居世界前列，并且超过了美国的医疗保健系统，尽管它占国内生产总值 (GDP) 的 10.3%，而美国则为 17.8%。维持这一排名在预算上具有挑战性。医学在不断发展，新的范式包括通过人工智能 (AI) 和机器学习 (ML) 利用大量数据来更好地筛查、诊断、预测、治疗和随访疾病的能力。这些工具可以显着降低成本。因此，加拿大不仅要准备好采用这些工具，而且要开发它们，这一点可能至关重要。加拿大在机器学习领域拥有卓越中心。该项目是满足上述两个目标的一个例子：1) 重要癌症生物标志物的优化（降低成本、改进 TAT），以及 2) 加强当地 ML 专业知识（研究、学生招募、潜在创业和改善当地经济）。