Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4217591 | Thoracic Surgery Clinics | 2007 | 9 Pages |
Abstract
Assessment of surgical risk in patients undergoing pulmonary resection is a fundamental goal for thoracic surgeons. Commonly available risk scores do not predict the individual outcome. Data mining and artificial neural networks are artificial intelligence mathematical models that have been used for estimation of prognosis in different clinical scenarios. When used to assess the surgical risk, they can integrate results from multiple data by predicting the individual outcome for patients rather than assigning them to less precise risk group categories.
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Authors
Hugo MD, Tomás G. MD, Ricardo O. PhD,