An innovative breakthrough in the early detection of cancer
El University Hospital of Fuenlabrada, located in the Community of Madrid, has taken an important step in the use of artificial intelligence (AI) to improve the early detection of cancer. In collaboration with the Infanta Leonor Hospital, the hospital is participating in a pioneering study called Clover, whose objective is to use AI to identify hidden cancer in patients who have suffered venous thrombotic events (VTE).
These types of events, although not always directly related to cancer, can be an early sign of the presence of undiagnosed tumors. In this regard, the study Clover It is key, since it uses a predictive model that combines the analysis of clinical data and Machine Learning to predict the likelihood that a patient will have hidden cancer. With an accuracy rate of 94%, this system is able to identify those patients who do not have tumors, thus avoiding unnecessary tests and offering faster and more accurate diagnoses.
Through this study, they have been analyzed More than 800 patients, detecting 56 Cases of Hidden Cancer (a 6.9% of the participants), with the most common tumors found in gastrointestinal, prostate and lung tracts In Men, and in the gastrointestinal, breast and hematological In women.
The integration of 15 clinical variables, which includes factors such as age, gender, blood pressure and analytical parameters such as D-dimer And the Hemoglobin, allows a detailed and personalized evaluation of each patient, increasing accuracy in prediction.
This progress has been recognized in the 2nd edition of the 'Ennova Health' Awards, which highlights its impact on the healthcare field and technological innovation applied to medicine.
In the coming months, the study will expand to Other Health Centers, which could allow the implementation of this predictive tool at the clinical level throughout the healthcare network.
This type of research underlines the importance of Artificial intelligence as a fundamental ally in the fight against cancer and opens new doors for early detection, which is essential for treatment and the improvement of patient outcomes.
