Organization of the database of patients with fungal infections and lung cancer to assist in the development of artificial intelligence tools applied to aid diagnosis in simple chest X-ray images

• Grant number: 23/09104-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2023
• End date: July 31, 2024
• Field of knowledge: Health Sciences - Medicine - Medical Radiology
• Principal Investigator: Marcel Koenigkam Santos
• Grantee: Plínio Takashi Karubi Palavicini Santos
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 19/22577-4 - Clinical application of artificial intelligence tools to diagnostic aid in simple chest radiography images, AP.JP

Abstract

Plain radiography (X-Ray) of the chest represents, in most situations, the first radiological examination in the evaluation of thoracic and pulmonary diseases. Most bronchopulmonary diseases appear on X-ray as opacities, such as tuberculosis, fungal infections, interstitial lung diseases, lung cancer and viral pneumonia. These diseases have high morbidity and mortality and require additional investigation, with computed tomography (CT) and/or laboratory tests. In recent years, computer aided diagnosis/detection (CAD) tools have been created to help detect alterations in imaging tests, interpret the findings and assist in the workflow of health services. . To this end, the development of artificial intelligence (AI), machine learning and deep learning tools has been highlighted. Fungal pneumonias are uncommon, but represent an important cause of morbidity and mortality, especially in the population of immunosuppressed individuals. Lung cancer is the main cause of cancer-related death in the world and, although screening should not be performed with X-rays, radiographic examination is often the first to detect the presence of a suspicious lung nodule or mass. The lung is also one of the most common sites for metastases from other tumors.