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方法。瓦里安医疗系统公司开发了一种癌症计划系统(称为360肿瘤学)，该系统提供决策支持，以生成从最初的癌症诊断到治疗后随访的整体护理路径。为了收集关于患者过去和现在诊断的完整医疗记录，该系统集成了来自传统信息系统的医疗信息，这会导致不准确和/或不完整的患者信息，从而影响癌症护理计划的准确性。该公司目前填补缺失信息的机制并不理想。该项目旨在开发和使用人工智能(AI)方法，通过对外部基于证据的医学知识资源进行推理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--称为似是而非推理，当面对不完整的知识时，它类似于人类的推理过程--来推断诊断和相关干预之间的医疗关系。这些推断的关系将提供缺失的信息。我们将使用真实世界的案例(由该公司提供)来评估研究成果，以确定基于人工智能的解决方案处理丢失临床信息的准确性和有效性。预计这种基于人工智能的方法将提高360肿瘤学在自动癌症护理规划方面的准确性，进而提高该公司在全球市场的竞争力。这项以加拿大为基础的推断医疗记录中缺失临床信息的新研究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。