Titlebook: International Conference on Innovative Computing and Communications; Proceedings of ICICC Aboul Ella Hassanien,Oscar Castillo,Ajay Jaiswal

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Mitanshi Rastogi,Meenu Vijarania,Neha Goelin which radiologists, pathologists, pulmonologists, surgeons, and medical and radiation oncologists discuss and reach a consensus on individualized imaging and treatment. The main objective of this chapter is to review the basic concepts related to the detection, staging, and follow-up of patients

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Shahanawaj Ahamad,Suryansh Bhaskar Talukdar,Rohit Anand,Veera Talukdar,Sanjiv Kumar Jain,Arpit Namdein which radiologists, pathologists, pulmonologists, surgeons, and medical and radiation oncologists discuss and reach a consensus on individualized imaging and treatment. The main objective of this chapter is to review the basic concepts related to the detection, staging, and follow-up of patients

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S. Janani,M. Sivarathinabala,Rohit Anand,Shahanawaj Ahamad,M. Ahmer Usmani,S. Mahabub BashaD) imaging method with the potential to overcome the main limitation of standard two-dimensional mammography, a masking effect due to overlapping fibroglandular breast tissue, improving diagnostic accuracy in breast cancer, particularly in dense breasts. CEM allows both a morphologic evaluation comp

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Poonam Rani,Devender Kumar,Nupur Sudhakar,Deepak Prakash,Shubhamize on the model performance by conducting a series of experiments on seven different dataset sizes. The findings indicate that our fine-tuned T5-based model outperformed other generative LLMs and Seq2Seq Models with a ROUGE-1 score of about 26.75, making it the selected baseline for this task. Our

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Narayan Kumar,Amit Kumar, the time of motion in the area between barriers becomes longer than that needed to surmount each of them. In other words, the barriers are of no importance for the discussion of the rate of deformation. Accordingly, such a linear visco-elastic deformation may be put aside in the present discussion

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,Joint Identification and Clustering Using Deep Learning Techniques,n Gaussian Mixture Model. The joint clusters obtained by the cluster models using three pose estimation models were comparable to and correlated to the anatomical model. However, they showed noticeable offsets and differences in sensitivity compared to those from the anatomical model. Overall, the j

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