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CliniScan+: An Integrated AI – Based Lung Disease Detection Diagnosis and Smart Healthcare Support System
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence, Medical domain
Abstract
lung diseases are among the major health conditions requiring timely diagnosis and appropriate medical consultation. Chest X-ray imaging is widely used as an initial diagnostic investigation; however, conventional analysis depends heavily on expert interpretation and may be time-consuming. Existing artificial intelligence-based diagnostic systems primarily focus on disease classification and often provide limited integration with healthcare support services. This paper presents CliniScan+, an integrated AI-based healthcare support system for lung disease detection using chest X-ray images. The proposed system employs a Convolutional Neural Network (CNN) for automated multi-disease classification and YOLOv11 for visual localization of relevant regions in chest X-ray images, thereby providing an interpretable representation of the model output. In addition to AI-based image analysis, the system incorporates a doctor recommendation module that assists users in identifying suitable medical specialists based on the predicted condition. A consultation tracking module maintains appointment and follow-up information to support continuity of healthcare services. The system is implemented using a Python-based backend and MongoDB for data management. The integration of disease classification, visual explanation, doctor recommendation, and consultation tracking provides a unified healthcare-support platform rather than an isolated prediction model. Experimental evaluation is performed using classification and detection metrics to assess the performance of the implemented models.
Keywords
Artificial Intelligence, Chest X-ray, Convolutional Neural Network, YOLOv11, Explainable AI, Lung Disease Detection, Healthcare Recommendation System, Consultation Tracking.
References
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How to cite this paper
@article{1723529,
author = {Rishika Sharma, Shiva Kumar Prajapathi H, Yudhil Krishna, Vedashree R, Dr. Latha P H},
title = {CliniScan+: An Integrated AI – Based Lung Disease Detection Diagnosis and Smart Healthcare Support System},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {3587-3597},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723529.pdf},
abstract = {lung diseases are among the major health conditions requiring timely diagnosis and appropriate medical consultation. Chest X-ray imaging is widely used as an initial diagnostic investigation; however, conventional analysis depends heavily on expert interpretation and may be time-consuming. Existing artificial intelligence-based diagnostic systems primarily focus on disease classification and often provide limited integration with healthcare support services.
This paper presents CliniScan+, an integrated AI-based healthcare support system for lung disease detection using chest X-ray images. The proposed system employs a Convolutional Neural Network (CNN) for automated multi-disease classification and YOLOv11 for visual localization of relevant regions in chest X-ray images, thereby providing an interpretable representation of the model output. In addition to AI-based image analysis, the system incorporates a doctor recommendation module that assists users in identifying suitable medical specialists based on the predicted condition. A consultation tracking module maintains appointment and follow-up information to support continuity of healthcare services. The system is implemented using a Python-based backend and MongoDB for data management.
The integration of disease classification, visual explanation, doctor recommendation, and consultation tracking provides a unified healthcare-support platform rather than an isolated prediction model. Experimental evaluation is performed using classification and detection metrics to assess the performance of the implemented models.},
keywords = {Artificial Intelligence, Chest X-ray, Convolutional Neural Network, YOLOv11, Explainable AI, Lung Disease Detection, Healthcare Recommendation System, Consultation Tracking.},
month = {September},
}