Development and Validation of Artificial Intelligence-Assisted Cholangioscopy Model for Automatic Detection of Malignant Biliary Strictures: An Initial Experience

Developer and Code Author: Fritz Tuazon

Digital Image Classification on Cholangioscopy and Analysis Module (DICCA Module)

In the realm of modern technology, computers have revolutionized the way we perceive and analyze images. Through the lens of computer vision, these intricate digital systems decipher visual data by interpreting images as matrices of pixels. This transformative capability has paved the way for remarkable advancements in artificial intelligence, particularly within the realm of healthcare. Today, healthcare systems worldwide face unprecedented challenges in giving patients the best care possible while managing costs and resources. That's where artificial intelligence (AI) comes in as a game changer. AI uses computers to do tasks that normally require human intelligence, like recognizing patterns in data. Artificial intelligence stands as a transformative force, empowering healthcare professionals with enhanced diagnostic precision, streamlined workflows, and unparalleled insights derived from data. In this era of technological evolution, the convergence of AI and healthcare represents a paradigm shift, promising to revolutionize patient care, optimize resource allocation, and shape the future of medicine. With this, on my paper entitled Development and Validation of Artificial Intelligence-Assisted Cholangioscopy Model for Automatic Detection of Malignant Biliary Strictures: An Initial Experience, we will know how Digital Image Classification on Cholangioscopy and Analysis Module or (DICCA Module) was able to give a promising result in classifying Benign or Malignant Biliary strictures.