Deep Learning Applications in Pancreatic Cancer

Abstract

Pancreatic cancer is one of the most lethal gastrointestinal malignancies. Despite advances in cross-sectional imaging, chemotherapy, radiation therapy, and surgical techniques, the 5-year overall survival is only 12%. With the advent and rapid adoption of AI across all industries, we present a review of applications of DL in the care of patients diagnosed with PC. A review of different DL techniques with applications across diagnosis, management, and monitoring is presented across the different pathological subtypes of pancreatic cancer. This systematic review highlights AI as an emerging technology in the care of patients with pancreatic cancer.

Keywords: artificial intelligence; deep learning; pancreatic cancer.

Figure 1

Number of publications in a PubMed search using deep learning and pancreas as key terms from 2016–2023.

Figure 2

Relationship of AI, ML, and DL. Neural networks are a type of DL. Radiomics are a subset of ML algorithms [8].

Figure 3

Methodology of review article: deep neural network (DNN); generative adversarial network (GAN); large language model (LLM); support vector machine (SVM).

Figure 4

An example of a GAN showing the adversarial nature of generated images being scored by the discriminator as “fake” or “real” until the discriminator has been fooled, in essence creating fake images which can plausibly be considered as real [40].