A Novel AI-Based Medical Diagnostic Disease Prediction

Boda Aravind; Budati Sheela Koushi; Yerkala Shivani; Tanniru Sai Vamshi; D Archana; Dr.S.Ramchandra Reddy

A Novel AI-Based Medical Diagnostic Disease Prediction

Author(s)	Mr. Boda Aravind, Ms. Budati Sheela Koushi, Ms. Yerkala Shivani, Mr. Tanniru Sai Vamshi, Prof. D Archana, Dr.S.Ramchandra Reddy
Country	India
Abstract	The medical imaging is now an indelible part of the contemporary healthcare system, and it allows clinicians to identify, track, and manage a vast number of illnesses successfully. X-rays, Magnetic Resonance Imaging (MRI), and Computed Tomography (CT) scans are the technologies that give a detailed information of inner body structures and aid physicians in identifying abnormalities and devising the necessary treatment. Nevertheless, manual analysis makes it a time-consuming and difficult task because of the growing size and complexity of medical imaging data, which have put a considerable burden on radiologists and the medical care team. The project is the medical diagnostic system, powered by AI and based on the Convolutional Neural Networks (CNNs), that automatically identifies abnormalities in medical images with a high precision. The system accepts multi-modal medical imaging in the form of images, which means that it can analyze the images of various diagnostic modalities to provide more detailed and dependable clinical assessment. In order to enhance the transparency and clinical trust, the system uses Explainable Artificial Intelligence (XAI) methods, including Grad-CAM and LIME, which produce visual heatmaps, which illuminate significant areas of the image that the model uses to make predictions. It is implemented with sophisticated deep learning systems and models, such as TensorFlow, PyTorch, OpenCV, and MONAI, and trained on large-scale medical data sets, including ChestX-ray14 and MIMIC-CXR, with the help of the computing environments with the use of graphics cards. Through these technologies, the efficient training and real-time inference can be performed, which means that the system will be able to help healthcare professionals make more diagnostic decisions faster. Moreover, the HIPAA guidelines are followed to the letter, which guarantees the privacy of patient information, data safety, and ethical medical information utilization. On the whole, the solution proposed is expected to enhance the accuracy of the diagnosis, ease the workload of the medical specialists, and offer scalable, reliable, and available AI-based healthcare assistance systems to hospitals and other clinical settings
Keywords	Artificial Intelligence (AI), Medical Image Analysis, Convolutional Neural Networks (CNN), Medical Imaging, Multi-Modal Imaging, Explainable Artificial Intelligence (XAI), Grad-CAM, LIME, Deep Learning
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-07-06

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E-ISSN 2582-2160

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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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International Journal For Multidisciplinary Research

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A Novel AI-Based Medical Diagnostic Disease Prediction

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