Artificial Intelligence for Lung Cancer: A Review of Diagnostic and Therapeutic Applications

Samruddhi Bagal , Deepa Padwal , Manjusha Tatiya

Artificial Intelligence (AI), Lung Cancer, Machine Learning (ML), Deep Learning (DL), Nodule Detection Personalized Medicine, Radiomics, Reinforcement Learning, Generative Adversarial Networks (GANs), Clinical Workflow, Early Detection, Diagnostic Imaging, Predictive Analytics, Data Quality, Patient Outcomes

This review investigates how artificial intelligence (AI) is enhancing the diagnosis and treatment of lung cancer, a leading cause of fatalities linked to cancer. The study explores various AI methods, including machine learning (ML) and deep learning (DL), aimed at boosting the accuracy of lung cancer detection and treatment options. It focuses on the use of these techniques for identifying nodules, evaluating genomic data, and creating personalized medical plans. Key factors such as the performance of algorithms, data quality, and integration into clinical settings are analyzed to understand their influence on patient outcomes. A detailed review of recent advancements in AI applications and the challenges faced during their clinical adoption is included. By identifying existing research gaps and potential areas for growth, this review aims to support the ongoing evolution of lung cancer care through AI innovations.

Published Paper   E-Certificate

"Artificial Intelligence for Lung Cancer: A Review of Diagnostic and Therapeutic Applications", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 10, page no.c617-c624, October-2024, Available :https://ijnrd.org/papers/IJNRD2410273.pdf

Volume 9 Issue 10, October-2024

Pages : c617-c624

Paper Reg. ID: IJNRD_301547

Published Paper Id: IJNRD2410273

Downloads: 00030

Research Area: Humanities All

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2410273

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2410273

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition