国际标准期刊号: 2165-7092
Annette Lofft Crna
Pancreatic disorders encompass a spectrum of conditions affecting the pancreas, ranging from benign inflammatory processes to malignant neoplasms. The diagnosis and management of these disorders present significant clinical challenges due to their variable presentation, overlapping symptoms, and limited therapeutic options. Traditional diagnostic approaches often rely on imaging studies, histopathological examination, and biochemical tests, which may be time-consuming, invasive, and subject to interpretation variability. In recent years, Artificial Intelligence (AI) has emerged as a promising tool in the field of medical diagnostics, offering novel solutions to complex clinical problems. By capitalizing machine learning algorithms, deep learning networks, and computational models, AI systems can analyze vast amounts of medical data, identify patterns, and generate predictive insights with unprecedented accuracy and efficiency. In the context of pancreatic disorders, AI holds immense potential to enhance diagnostic accuracy, facilitate early detection, and guide personalized treatment strategies.