PDF(Pubmed)
Abstract：
BACKGROUND: According to the World Bank, Malaysia reported an estimated 97 tuberculosis cases per 100,000 people in 2021. Chest x-ray (CXR) remains the best conventional method for the early detection of pulmonary tuberculosis (PTB) infection. The intervention of artificial intelligence (AI) in PTB diagnosis could efficiently aid human interpreters and reduce health professionals\' work burden. To date, no AI studies have been evaluated in Malaysia.
OBJECTIVE: This study aims to evaluate the performance of Putralytica and Qure.ai software for CXR screening and PTB diagnosis among the Malaysian population.
METHODS: We will conduct a retrospective case-control study at the Respiratory Medicine Institute, National Cancer Institute, and Sungai Buloh Health Clinic. A total of 1500 CXR images of patients who completed treatments or check-ups will be selected and categorized into three groups: (1) abnormal PTB cases, (2) abnormal non-PTB cases, and (3) normal cases. These CXR images, along with their clinical findings, will be the reference standard in this study. All patient data, including sociodemographic characteristics and clinical history, will be collected prior to screening via Putralytica and Qure.ai software and readers\' interpretation, which are the index tests for this study. Interpretation from all 3 index tests will be compared with the reference standard, and significant statistical analysis will be computed.
RESULTS: Data collection is expected to commence in August 2023. It is anticipated that 1 year will be needed to conduct the study.
CONCLUSIONS: This study will measure the accuracy of Putralytica and Qure.ai software and whether their findings will concur with readers\' interpretation and the reference standard, thus providing evidence toward the effectiveness of implementing AI in the medical setting.
UNASSIGNED: PRR1-10.2196/36121.
OBJECTIVE: This study aims to evaluate the performance of Putralytica and Qure.ai software for CXR screening and PTB diagnosis among the Malaysian population.
METHODS: We will conduct a retrospective case-control study at the Respiratory Medicine Institute, National Cancer Institute, and Sungai Buloh Health Clinic. A total of 1500 CXR images of patients who completed treatments or check-ups will be selected and categorized into three groups: (1) abnormal PTB cases, (2) abnormal non-PTB cases, and (3) normal cases. These CXR images, along with their clinical findings, will be the reference standard in this study. All patient data, including sociodemographic characteristics and clinical history, will be collected prior to screening via Putralytica and Qure.ai software and readers\' interpretation, which are the index tests for this study. Interpretation from all 3 index tests will be compared with the reference standard, and significant statistical analysis will be computed.
RESULTS: Data collection is expected to commence in August 2023. It is anticipated that 1 year will be needed to conduct the study.
CONCLUSIONS: This study will measure the accuracy of Putralytica and Qure.ai software and whether their findings will concur with readers\' interpretation and the reference standard, thus providing evidence toward the effectiveness of implementing AI in the medical setting.
UNASSIGNED: PRR1-10.2196/36121.
摘要：
背景：根据世界银行的数据，马来西亚报告称，2021年每10万人中估计有97例肺结核病例。胸部X线（CXR）仍然是早期发现肺结核（PTB）感染的最佳常规方法。人工智能（AI）在PTB诊断中的干预可以有效地帮助人类口译员并减轻卫生专业人员的工作负担。迄今为止,马来西亚尚未评估AI研究。
目的：本研究旨在评估Putralytica和Qure的性能。用于马来西亚人群中CXR筛查和PTB诊断的ai软件。
方法：我们将在呼吸医学研究所进行回顾性病例对照研究，国家癌症研究所,和SungaiBuloh健康诊所。将选择完成治疗或检查的患者的总共1500张CXR图像，并将其分为三组：（1）异常PTB病例，（2）非PTB异常病例，（3）正常情况。这些CXR图像，连同他们的临床发现，将作为本研究的参考标准。所有患者数据,包括社会人口统计学特征和临床病史，将在通过Putralytica和Qure进行筛查之前收集。人工智能软件和读者解释，这是这项研究的指标测试。所有3个指标测试的解释将与参考标准进行比较，和重要的统计分析将被计算。
结果：数据收集预计将于2023年8月开始。预计将需要一年的时间来进行这项研究。
结论：这项研究将测量Putralytica和Qure的准确性。人工智能软件及其发现是否与读者的解释和参考标准一致，从而为在医疗环境中实施人工智能的有效性提供了证据。
■PRR1-10.2196/36121。
目的：本研究旨在评估Putralytica和Qure的性能。用于马来西亚人群中CXR筛查和PTB诊断的ai软件。
方法：我们将在呼吸医学研究所进行回顾性病例对照研究，国家癌症研究所,和SungaiBuloh健康诊所。将选择完成治疗或检查的患者的总共1500张CXR图像，并将其分为三组：（1）异常PTB病例，（2）非PTB异常病例，（3）正常情况。这些CXR图像，连同他们的临床发现，将作为本研究的参考标准。所有患者数据,包括社会人口统计学特征和临床病史，将在通过Putralytica和Qure进行筛查之前收集。人工智能软件和读者解释，这是这项研究的指标测试。所有3个指标测试的解释将与参考标准进行比较，和重要的统计分析将被计算。
结果：数据收集预计将于2023年8月开始。预计将需要一年的时间来进行这项研究。
结论：这项研究将测量Putralytica和Qure的准确性。人工智能软件及其发现是否与读者的解释和参考标准一致，从而为在医疗环境中实施人工智能的有效性提供了证据。
■PRR1-10.2196/36121。
