EC Pulmonology and Respiratory Medicine

Venous thromboembolism (VTE) is a grave medical condition comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), both of which pose significant threats to patient health and wellbeing. While DVT primarily affects deep veins, particularly in the lower limbs, PE arises when a blood clot dislodges and travels to the pulmonary artery, potentially leading to fatal consequences. The clinical ramifications of VTE are profound, as it ranks among the leading causes of mortality and morbidity worldwide. PE, a severe complication of VTE, manifests with symptoms such as dyspnea, chest pain and haemoptysis, often resulting in life-threatening situations. Conversely, DVT can lead to chronic pain, swelling and even limb dysfunction in severe cases. Given the gravity of VTE, timely diagnosis and prevention are paramount. Consequently, the exploration of early warning systems and clinical decision support mechanisms for VTE holds immense significance in enhancing patient survival rates and mitigating associated complications. In this context, our critical care department, with support from the Science and Technology Bureau, has developed a VTE clinical decision support system leveraging Artificial Intelligence (AI). The system, currently in the testing phase, aims to provide a secure and reliable platform for early diagnosis and treatment decision-making. By harnessing AI technology, we endeavour to improve the accuracy of VTE risk assessment and streamline clinical management protocols, ultimately advancing patient outcomes. The most important part of this system is to input standardized VTE patients, and this case report is one of the standardized patients that is selected and input for the system to automatically recognize and learn.

 Keywords: Venous Thromboembolism (VTE); Deep Vein Thrombosis (DVT); Pulmonary Embolism (PE); Artificial Intelligence (AI)

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