Artificial intelligence-based solution designed to predict the risk of occult cancer in patients who have suffered a venous thromboembolism (VTE). It uses machine learning models to identify clinical patterns that could anticipate an oncological diagnosis within 2 years of the thrombotic event, thus facilitating earlier and more targeted detection.
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Venous thromboembolism may, in many cases, be the first sign of undiagnosed cancer. However, there are no effective clinical tools to accurately determine which patients are at increased risk of developing cancer after VTE. This creates clinical uncertainty and can lead to both overdiagnosis and delayed diagnoses. CLOVER addresses this challenge by using artificial intelligence to stratify oncologic risk on an individualized basis and support medical decision making.
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