Using AI-based Plausible Reasoning for Inferring Missing Knowledge to Provide Automated Decision Support

使用基于人工智能的合理推理来推断缺失的知识以提供自动决策支持

• 批准号: 543806-2019
• 负责人: Abidi, SyedSibteRaza
• 金额: $ 1.82万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681282
• 关键词: Using; AI; based; Plausible; Reasoning

Cancer treatment planning requires complete patient information, including all medical conditions and therapies. Varian Medical Systems has developed a cancer planning system (called 360 Oncology) which offers decision support to generate a holistic care path from initial cancer diagnosis to post-treatment follow-up. To gather a complete medical record on the patient's past and present diagnoses, the system integrates medical information from legacy information systems which leads to inaccurate and/or incomplete patient information that affects the accuracy of the cancer care plan. The company's current mechanisms to fill in the missing information are sub-optimal. This project aims to develop and use Artificial Intelligence (AI) methods to infer the missing clinical information within a medical record by reasoning over external evidence-based medical knowledge resources. The project will investigate a novel approach-called plausible reasoning that is similar to human reasoning processes when confronted with incomplete knowledge--to infer medical relationships between diagnoses and associated interventions. These inferred relationships will provide the missing information. We will evaluate the research output with real-world cases (provided by the company) to determine the accuracy and efficacy of the AI based solution to handling missing clinical information. It is anticipated that this AI based method will improve 360 Oncology's accuracy of automated cancer care planning, and, in turn, increase the company's competitiveness in the global marketplace. This novel Canadian based research to infer missing clinical information in medical records has benefits to the Canadian healthcare sector, as the technology can be applied to other patient support system to improve the quality of information in medical records.

癌症治疗计划需要完整的患者信息，包括所有的医疗条件和治疗。Varian Medical Systems开发了一个癌症规划系统（称为360 Oncology），该系统提供决策支持，以生成从初始癌症诊断到治疗后随访的整体护理路径。为了收集关于患者的过去和当前诊断的完整医疗记录，系统整合来自遗留信息系统的医疗信息，这导致影响癌症护理计划的准确性的不准确和/或不完整的患者信息。该公司目前填补缺失信息的机制是次优的。该项目旨在开发和使用人工智能（AI）方法，通过推理外部循证医学知识资源来推断病历中缺失的临床信息。该项目将研究一种新的方法，称为合理推理，类似于人类在面对不完整知识时的推理过程，以推断诊断和相关干预措施之间的医学关系。这些推断的关系将提供缺失的信息。我们将使用真实案例（由公司提供）评估研究结果，以确定基于AI的解决方案在处理缺失临床信息方面的准确性和有效性。预计这种基于人工智能的方法将提高360 Oncology自动癌症护理计划的准确性，从而提高公司在全球市场的竞争力。这项新的加拿大研究推断医疗记录中缺失的临床信息对加拿大医疗保健部门有利，因为该技术可以应用于其他患者支持系统，以提高医疗记录中的信息质量。