ANNCRIPS: Artificial Neural Networks for Cancer Research In Prediction &
  Survival
Amit Mathapati
Prostate cancer is a prevalent malignancy among men aged 50 and older.
Current diagnostic methods primarily rely on blood tests, PSA:Prostate-Specific
Antigen levels, and Digital Rectal Examinations (DRE). However, these methods
suffer from a significant rate of false positive results. This study focuses on
the development and validation of an intelligent mathematical model utilizing
Artificial Neural Networks (ANNs) to enhance the early detection of prostate
cancer. The primary objective of this research paper is to present a novel
mathematical model designed to aid in the early detection of prostate cancer,
facilitating prompt intervention by healthcare professionals. The model's
implementation demonstrates promising potential in reducing the incidence of
false positives, thereby improving patient outcomes. Furthermore, we envision
that, with further refinement, extensive testing, and validation, this model
can evolve into a robust, marketable solution for prostate cancer detection.
The long-term goal is to make this solution readily available for deployment in
various screening centers, hospitals, and research institutions, ultimately
contributing to more effective cancer screening and patient care.