AI model predicts pulmonary Long COVID with 94% accuracy using hospital data
Researchers have developed machine learning algorithms that can identify which COVID patients will develop serious lung complications months after infection, using only data collected during their initial hospital stay. The ability to predict these outcomes early could enable targeted interventions and reduce long-term disability, with significant implications for healthcare systems managing millions of post-COVID patients.
Originaltitel: Machine learning predicts pulmonary Long Covid sequelae using clinical data
<p>Long COVID is a multi-systemic disease characterized by the persistence or occurrence of many symptoms that in many cases affect the pulmonary system. These, in turn, may deteriorate the patient’s quality of life making it easier to develop severe complications. Being able to predict this syndrome is therefore important as this enables early treatment. In this work, we investigated three machine learning approaches that use clinical data collected at the time of hospitalization to this goal. The first works with all the descriptors feeding a traditional shallow learner, the second exploits the benefits of an ensemble of classifiers, and the third is driven by the intrinsic multimodality of the data so that different models learn complementary information. The experiments on a new cohort of data from 152 patients show that it is possible to predict pulmonary Long Covid sequelae with an accuracy of up to 94%. As a further contribution, this work also publicly discloses the related data repository to foster research in this field.</p>