Optimized-ANN Approach for Enhanced Lung Cancer Diagnosis: A Machine Learning-Integrated Methodology-Reference-Cited by-同舟云学术

Optimized-ANN Approach for Enhanced Lung Cancer Diagnosis: A Machine Learning-Integrated Methodology

Published:2023-11-23 Issue: Volume:74 Page:1-6
ISSN:
Container-title:Proceedings of the 5th International Conference on Information Management & Machine Intelligence
language:
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Author:

R Balamanigandan¹^ORCID,R Mahaveerakannan²^ORCID,Dadheech Pankaj³^ORCID,R Bhavani²^ORCID,R Dhanalakshmi²^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Saveeth School of Engineering, Saveeth Institute of Medical and Technical Science, Saveetha University, India

2. Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, India

3. Department of Computer Science & Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT), India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3647444.3652448

Reference13 articles.

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3. ) Demondion Emilie Olivier Ernst Alexandre Louvet Benjamin Robert Galit Kafri Eran Langzam and Mathilde Vermersch. 2023. “Hepatic Fat Quantification in Dual-Layer Computed Tomography Using a Three-Material Decomposition Algorithm.” European Radiology November. https://doi.org/10.1007/s00330-023-10382-z.

4. Prospective Evaluation of Quantitative F-18-FDG-PET/CT for Pre-Operative Thoracic Lymph Node Staging in Patients with Lung Cancer as a Target for Computer-Aided Diagnosis

5. ) Higgins Kristin Jessy Deshane and Fiona Hegi-Johnson. 2023. Factors That Impact the Survival of Non-Small Cell Lung Cancer. Frontiers Media SA.