International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Web-based AI Platform for Early Cancer Detection through Histopathological Image Analysis

Author(s) Vaibhav Vudayagiri
Country United States
Abstract This article presents an innovative web-based artificial intelligence platform designed to revolutionize
early cancer detection through advanced histopathological image analysis.The solution addresses critical
challenges in traditional cancer diagnostics, where manual analysis faces limitations of inter-observer
variability and time constraints. The platform leverages state-of-the-art convolutional neural networks,
specifically a modified ResNet-152 architecture enhanced with attention mechanisms, to provide accurate
and efficient cancer detection capabilities. The article demonstrates exceptional clinical performance,
achieving 94.8% sensitivity (95% CI: 93.2-96.4%) and 92.3% specificity (95% CI: 90.7-93.9%) in
comprehensive validation studies across five independent medical centers. This represents a 35%
improvement in diagnostic accuracy compared to traditional methods. The platform processes
high-resolution histopathological images (up to 100,000 x 100,000 pixels) with an average processing
time of 45 seconds per case, enabling real-time analysis and rapid diagnosis
Keywords Keywords: Histopathological Image Analysis; Convolutional Neural Networks; Cancer Detection; Digital Pathology; Healthcare Security
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-04
Cite This Web-based AI Platform for Early Cancer Detection through Histopathological Image Analysis - Vaibhav Vudayagiri - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32240
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.32240
Short DOI https://doi.org/g8tv8q
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