Developing a Digital Twin for Prostate Cancer Diagnosis using Neuro-Symbolic AI and Convolutional Neural Networks: A Comprehensive Walkthrough

Foreword

Prostate cancer is a pervasive health challenge, representing one of the leading causes of cancer-related deaths among men globally. Early detection and accurate diagnosis are critical for effective treatment and improved patient outcomes.

In this pursuit, I began to create the integration of Neuro-Symbolic AI with Convolutional Neural Networks (CNNs) which offers a promising frontier. This comprehensive walkthrough dives into the development of a Digital Twin for prostate cancer diagnosis, dissecting the underlying mathematics, meticulously analyzing the code implementation, exploring diverse use cases, elucidating the manifold benefits, and scrutinizing the compelling results achieved.

Introduction

The convergence of Neuro-Symbolic AI and Convolutional Neural Networks (CNNs) marks a significant advancement in the realm of medical diagnostics. This project aims to construct a Digital Twin for prostate cancer diagnosis, an intricate virtual model that mirrors the physiological and pathological attributes of the prostate gland. By harnessing the strengths of both symbolic reasoning and deep learning, the…