IMPROVING THE ACCURACY OF HISTOPATHOLOGICAL DIAGNOSIS IN BREAST CANCER USING ARTIFICIAL INTELLIGENCE

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Fatma Salum Said Al Battashy; Mr. Abdulrahman Banisheyba; k. s rana; Dr. Pankaj kaul; Abba Umar; Sabrina Masoud

IMPROVING THE ACCURACY OF HISTOPATHOLOGICAL DIAGNOSIS IN BREAST CANCER USING ARTIFICIAL INTELLIGENCE

Authors: Fatma Salum Said Al Battashy, Mr. Abdulrahman Banisheyba, k. s rana, Dr. Pankaj kaul, Abba Umar, Sabrina Masoud

Unique Paper ID: 171191
Volume: 11
Issue: 7
PageNo: 3708-3711

Keywords: No Keywords Found

Abstract:
This study explores how artificial intelligence (AI) can improve the accuracy of histopathological diagnosis for breast cancer. Conducted in the Zanzibar Urban West region, the research evaluates AI’s effectiveness by analyzing tissue slides using advanced computer vision techniques. Both qualitative and quantitative methods of data collection were used, including interviews, observation checklists, and experiments involving patient samples, doctors, and AI specialists. The findings highlight the critical role of histopathological diagnosis in guiding treatment decisions and influencing patient outcomes. While traditional diagnostic processes are effective, they are prone to limitations such as subjectivity and variability. AI integration offers the promise of improved accuracy, consistency, and efficiency. Despite challenges and ethical considerations, the study underscores the potential of AI to revolutionize histopathology diagnosis, paving the way for enhanced disease diagnosis accuracy in healthcare.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 7
PageNo: 3708-3711

IMPROVING THE ACCURACY OF HISTOPATHOLOGICAL DIAGNOSIS IN BREAST CANCER USING ARTIFICIAL INTELLIGENCE

Available:https://ijirt.org/article?manuscript=171191

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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