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Design, Development and Deployment of Deep Learning (Ensemble) Model for Lung Cancer Detection: A Retrospective Study

Funded Research Project

Under

Indian Council of Medical Research

Department of Health Research and Family Welfare, Government of India

(Sanctioned Under IIRP Scheme 2023-2024 vide Grant No: EM/SG/Dev. Res/120/0847-2023)

Principal Investigator:Dr. Subrata Sinha

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

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PulmoNet
AI-Powered Diagnosis
Research Slide 1

Advanced AI-Powered Lung Cancer Detection

Pioneering cutting-edge CNN technology for precise lung cancer classification and early detection

Advanced AI-PoweredLung Cancer Detection

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

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About Our Project

We are developing an advanced Convolutional Neural Network (CNN) ensemble model to achieve highly accurate classification of lung cancer from Whole Slide Images (WSI) and microscopic images, enabling early detection and improved patient outcomes.

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.

Project Timeline

Feb - April 2024
Project Inception & Team Formation

ICMR grant approved, scientists appointed, and medical doctors allocated to the research team

May - Aug 2024
Data Collection Phase

Collection of WSI and microscopic images from collaborating medical institutions

Sept - Nov 2024
Data Extraction & Preprocessing

Image annotation, feature extraction, and dataset preparation for model training

Dec 2024 - March 2025
Model Development & Training

CNN ensemble architecture design, deep learning model training, optimization, and validation

April - Sept 2025
Web Platform Development

Development of PulmoNet web application for model deployment and accessibility

Present
Continuous Improvement

Ongoing model refinement, accuracy enhancement, and platform feature expansion

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.

Our Vision

Dr. Subrata Sinha

Dr. Subrata Sinha

Principal Investigator

Professor, Department of Computational Sciences

Brainware University

Our mission is to revolutionize lung cancer detection through cutting-edge artificial intelligence. By developing advanced deep learning models, we aim to enable earlier diagnosis, improve treatment outcomes, and ultimately save lives.

This ICMR-funded research project represents a significant step toward making world-class diagnostic tools accessible to healthcare providers across India. We envision a future where AI-powered medical imaging becomes an integral part of routine cancer screening, helping doctors make faster and more accurate diagnoses.

Through collaboration with leading oncologists, pathologists, and medical institutions, we are building a system that combines the precision of artificial intelligence with the expertise of human clinicians, setting new standards in healthcare innovation.

Get in Touch

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

Contact Information

Email

subratasinha2020@gmail.com

Location

Brainware University
Barasat, West Bengal

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