Publications by authors named "Gracinda R Guerreiro"
Background: Current prognosis in oncology is reduced to the tumour stage and performance status, leaving out many other factors that may impact the patient´s management. Prognostic stratification of early stage non-small-cell lung cancer (NSCLC) patients with poor prognosis after surgery is of considerable clinical relevance. The objective of this study was to identify clinical factors associated with long-term overall survival in a real-life cohort of patients with stage I-II NSCLC and develop a prognostic model that identifies features associated with poor prognosis and stratifies patients by risk.
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- Artificial intelligence (AI) has shown promise in addressing biomedical issues like cancer, but tools that significantly impact oncology are limited; this study aims to create an AI tool to analyze cancer patient data and identify key clinical factors affecting prognosis.
- The researchers analyzed clinical data from 5,275 patients with non-small cell lung cancer, breast cancer, and non-Hodgkin lymphoma, incorporating data from wearable devices and quality of life questionnaires.
- The developed AI tool successfully categorized patients into low and high-risk profiles based on survival probabilities, demonstrating its potential for enhancing risk stratification and improving clinical management of cancer patients.