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Case Study

Healthcare

Ingestion and Summarization: The chatbot ingests and summarizes critical documents such as SOPs, batch records, and equipment manuals, providing instant access to relevant information.

Business Challenges

Auto diagnosis based on X-Ray images Medical imaging, particularly chest X-rays, plays a critical role in diagnosing various conditions. However, traditional diagnostic methods often lead to inefficiencies, such as high radiologist workload, delayed diagnosis, and inconsistent interpretations.

CBC Solutions

We implemented an AI-powered system, CBC’s X-Ray Classifier, designed specifically for multi-label classification of chest X-ray images. This innovative tool integrates advanced deep learning, convolutional neural networks (CNN), and pre-processing algorithms to enhance diagnostic accuracy and efficiency.

Benefits realized by Customer

Automated Image Analysis: • Multi-Label Classification: The AI model, trained on the NIH Chest X-ray dataset, accurately classifies 15 conditions such as pneumonia, pleural effusion, cardiomegaly, and fibrosis from a single X-ray. User-Friendly Interface: • Visual Insights: Provides Scan Findings by uploading the X-Ray images.

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