Harnessing AI for precision tonsillitis diagnosis: a revolutionary approach in endoscopic analysis.

Background: Diagnosing and treating tonsillitis pose no significant challenge for otolaryngologists; however, it can increase the infection risk for healthcare professionals amidst the coronavirus pandemic. In recent years, with the advancement of artificial intelligence (AI), its application in medical imaging has also thrived. This research is to identify the optimal convolutional neural network (CNN) algorithm for accurate diagnosis of tonsillitis and early precision treatment.

Clinical Relevance of Urine Flow Rate and Exposure to Polycyclic Aromatic Hydrocarbons.

Background: Polycyclic aromatic hydrocarbon (PAH) metabolites have received increasing attention because several of these organic substances are highly carcinogenic or mutagenic. Exposure to PAHs is associated with many harmful health effects; however, we are not aware of any study that has explored the exposure to PAHs and urinary conditions in the general population. The present work aimed to investigate the correlation among PAH and urine flow rate (UFR).