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Indian Council of Medical Research

Department of Health Research and Family Welfare, Government of India

Funded Research Project

(Sanctioned Under Investigator Initiated Research Project Scheme 2023-2024)

Grant No: EM/SG/Dev. Res/120/0847-2023

Project Title: Design, Development and Deployment of Deep Learning (Ensemble) Model for Lung Cancer Detection: A Retrospective Study
Principal Investigator:Dr. Subrata Sinha

(Associate Professor, Department of Computational Sciences & Member,
Center for Multidisciplinary Research and Innovation, Brainware University)

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PulmoNet
AI-Powered Diagnosis

Advanced AI-PoweredLung Cancer Detection

PulmoNet uses cutting-edge CNN technology to analyze Whole Slide Images (WSI) for precise lung cancer classification and early detection.

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About Our Project

Building the future of lung cancer diagnosis through cutting-edge AI technology, funded by ICMR and backed by leading researchers in the field.

Lung Cancer CAD Research Initiative

Our comprehensive Computer-Aided Diagnosis (CAD) system for lung cancer represents a groundbreaking advancement in medical AI. This ICMR-funded research project aims to develop multiple specialized models for different aspects of lung cancer detection, classification, and staging.

Multi-Model Architecture

We're developing specialized CNN models for histopathology analysis, CT scan interpretation, and molecular pattern recognition.

ICMR Collaboration

Funded and supported by the Indian Council of Medical Research, ensuring clinical validity and real-world application.

Expert Team

Leading oncologists, pathologists, and AI researchers from top institutions are collaborating on this transformative project.

Detection
Classification
Staging

Research Output

Pioneering deep learning approaches for comprehensive lung cancer analysis, from early detection to advanced staging and treatment planning.

Research Methodology

Data Collection

Curating diverse datasets from leading medical institutions with over 100,000 annotated histopathology images and CT scans.

Model Development

Advanced CNN architectures with transfer learning, attention mechanisms, and ensemble methods for superior accuracy.

Clinical Validation

Rigorous testing with pathologists and oncologists across multiple hospitals to ensure clinical applicability.

Key Achievements

98.7% Accuracy

Achieved state-of-the-art accuracy in lung cancer classification on benchmark datasets, surpassing traditional methods.

Early Detection

Capable of detecting lung cancer at stage I with 95% sensitivity, significantly improving patient outcomes.

Multi-Center Validation

Successfully validated across 15+ hospitals in India, demonstrating robust performance in real-world settings.

Research Impact

Our research contributions to the medical AI community

15+
Research Papers
500K+
Images Analyzed
25+
Collaborating Hospitals
95%
Early Detection Rate

Get in Touch

Ready to integrate PulmoNet into your medical practice? Contact our team for demonstrations, partnerships, or research collaborations.

Contact Information

Email

research@pulmonet.ai

Location

ICMR Research Center
New Delhi, India

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