• Shaik Mahaboob Basha
• K. Deepthika
• N. Ganesh
• M. Javed Akbar
• M. Meghanadham Reddy

The Internet of Medical Things (IoMT) is a collection of medical devices and related products. An application that connects health IT systems through an Internet computer network and mood. In terms of diagnosis, medical condition classification plays an important role in the prediction and early diagnosis of serious diseases. Death medical imaging is an important part of a patient's medical record and can be used internally for management, control and treatment of diseases. However, classifying images on a computer is a difficult task analysis. In this research paper, we introduce a more efficient and deep learning classifier (DL) for lung cancer classification, brain imaging and Alzheimer's disease. Researchers think Set up Preprocessing, feature selection and classification. The main goal of writing this is to get the best results. A feature selection model for good health image classification. DL performance will improve. In the classifications, a kernel search (OCS) algorithm is considered. Selection of OCS algorithm. The best features of the image are pre-processing, here select the multi-textured, grainy features analysis. Finally, the best features improve classification results and improve accuracy, specificity and sensitivity of medical imaging analysis. The expected results have been achieved by MATLAB and comparison with feature selection models and other classification methods. Here, the proposed model achieves high performance in terms of accuracy, sensitivity and specificity For the set of images requested, it was 95.22%, 86.45% and 100%.

IOT, Detection, Image classification, Deep Learning

"Deep Learning Model-Based Optimal Feature Selection For Medical Image Classification In The Internet Of Medical Things", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.d306-d311, May-2024, Available :http://www.jetir.org/papers/JETIR2405332.pdf

"Deep Learning Model-Based Optimal Feature Selection For Medical Image Classification In The Internet Of Medical Things", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppd306-d311, May-2024, Available at : http://www.jetir.org/papers/JETIR2405332.pdf