From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer

• Published in: Diagnostics (Basel) Vol. 14; no. 2; p. 174
• Main Authors: Tripathi, Satvik, Tabari, Azadeh, Mansur, Arian, Dabbara, Harika, Bridge, Christopher P., Daye, Dania
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.01.2024
• Subjects: Algorithms; Artificial intelligence; artificial intelligence (AI); artificial neural network (ANN); Cancer; Cancer research; Care and treatment; Clinical outcomes; Clustering; Computational linguistics; Datasets; Deep learning; Diagnosis; Disease; Electronic health records; Forecasts and trends; future perspectives; Health care reform; Language processing; Machine learning; machine learning (ML); Medical coding; Medical imaging; Medical imaging equipment; Medical personnel; Medical prognosis; Medical research; Natural language interfaces; Natural language processing; Neural networks; pancreatic adenocarcinoma (PAC); Pancreatic cancer; Patient outcomes; Patients; Precision medicine; Prognosis; review; Support vector machines; Tomography; Tumors; artificial neural network (ANN); machine learning (ML); pancreatic adenocarcinoma (PAC); artificial intelligence (AI); review; future perspectives
• ISSN: 2075-4418; 2075-4418
• DOI: 10.3390/diagnostics14020174

Pancreatic cancer is a highly aggressive and difficult-to-detect cancer with a poor prognosis. Late diagnosis is common due to a lack of early symptoms, specific markers, and the challenging location of the pancreas. Imaging technologies have improved diagnosis, but there is still room for improvement in standardizing guidelines. Biopsies and histopathological analysis are challenging due to tumor heterogeneity. Artificial Intelligence (AI) revolutionizes healthcare by improving diagnosis, treatment, and patient care. AI algorithms can analyze medical images with precision, aiding in early disease detection. AI also plays a role in personalized medicine by analyzing patient data to tailor treatment plans. It streamlines administrative tasks, such as medical coding and documentation, and provides patient assistance through AI chatbots. However, challenges include data privacy, security, and ethical considerations. This review article focuses on the potential of AI in transforming pancreatic cancer care, offering improved diagnostics, personalized treatments, and operational efficiency, leading to better patient outcomes.