The Role of Artificial Intelligence in Diagnosing Prostate Cancer Through Histopathology

EasyChair Preprint 15345

Abstract

Prostate cancer is one of the most prevalent cancers affecting men globally, emphasizing the critical need for early and accurate diagnosis. Histopathology, the gold standard for cancer diagnosis, faces challenges such as variability in interpretation and workload constraints for pathologists. This article explores the integration of artificial intelligence (AI) in histopathological diagnosis, highlighting its potential to enhance accuracy, efficiency, and consistency in identifying prostate cancer. We examine the types of AI technologies utilized, including machine learning and deep learning, and discuss their reliance on high-quality data from histopathological image databases and clinical records. Current applications and case studies illustrate the effectiveness of AI tools in improving diagnostic outcomes. However, the adoption of AI also raises challenges, including data quality, ethical considerations, and resistance from traditional practitioners. Looking ahead, the article emphasizes the importance of collaboration between AI developers and healthcare professionals to address these challenges and harness AI's potential in transforming prostate cancer diagnosis. Ultimately, the integration of AI in histopathology promises to enhance early detection, personalize treatment strategies, and improve overall patient care in the fight against prostate cancer.

Keyphrases: Current application, Histopathology, prostate cancer

@booklet{EasyChair:15345,
  author    = {George Christopher and Victor John and Taye Kehinde},
  title     = {The Role of Artificial Intelligence in Diagnosing Prostate Cancer Through Histopathology},
  howpublished = {EasyChair Preprint 15345},
  year      = {EasyChair, 2024}}