Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer

SIMPLE SUMMARY: Pancreatic cancer poses a grave threat to mankind, due to its poor prognosis and aggressive nature. An accurate diagnosis is critical for implementing a successful treatment plan given the risk of exacerbation. The diagnosis of pancreatic cancer relies on medical imaging, which provides inaccurate information about the prognosis of the patient and makes it difficult for clinicians to select the optimal treatment. Data derived from medical imaging has been integrated with artificial intelligence, an emerging technology, to facilitate clinical decision making. This review explores the implementation of artificial intelligence for various imaging modalities to obtain a precise cancer diagnosis. ABSTRACT: Pancreatic cancer is among the most challenging forms of cancer to treat, owing to its late diagnosis and aggressive nature that reduces the survival rate drastically. Pancreatic cancer diagnosis has been primarily based on imaging, but the current state-of-the-art imaging provides a poor prognosis, thus limiting clinicians’ treatment options. The advancement of a cancer diagnosis has been enhanced through the integration of artificial intelligence and imaging modalities to make better clinical decisions. In this review, we examine how AI models can improve the diagnosis of pancreatic cancer using different imaging modalities along with a discussion on the emerging trends in an AI-driven diagnosis, based on cytopathology and serological markers. Ethical concerns regarding the use of these tools have also been discussed.