International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

An Augmentation in the Diagnostic Potency of Breast Cancer through a Deep Learning Cloud-Based A.I. Framework to Compute Tumor Malignancy and Risk

Om AgarwalGrade 10 Student @ Citadel High School, Halifax, Nova Scotia, Canada

Vol 3 No 6 (2019): Volume 3, Issue 6, June 2019 | Pages: 1-24

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 01-06-2019

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Abstract

This research project focuses on developing a web-based multi-platform solution for augmenting prognostic strategies to diagnose breast cancer (BC), from a variety of different tests, including histology, mammography, cytopathology, and fine-needle aspiration cytology, all in an automated fashion. The respective application utilizes tensor-based data representations and deep learning architectural algorithms, to produce optimized models for the prediction of novel instances against each of these medical tests. This system has been designed in a way that all of its computation can be integrated seamlessly into a clinical setting, without posing any disruption to a clinician’s productivity or workflow, but rather an enhancement of their capabilities. This software can make the diagnostic process automated, standardized, faster, and even more accurate than current benchmarks achieved by both pathologists, and radiologists, which makes it invaluable from a clinical standpoint to make well-informed diagnostic decisions with nominal resources.

Keywords

Breast Cancer, Early Detection, Improved Diagnostics, Deep Learning, AI, Histology, Cytopathology, Mammography, Fine-Needle Aspiration Cytology


Citation of this Article

Citation of this article:

Om Agarwal, “An Augmentation in the Diagnostic Potency of Breast Cancer through A Deep Learning Cloud-Based A.I. Framework to Compute Tumor Malignancy & Risk” Published in International Research Journal of Innovations in Engineering and Technology (IRJIET), Volume 3, Issue 6, pp 1-24, June 2019.

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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