Author
Malathi Ravindran, R.
AI-Driven Segmentation of Chest Radiographs for Enhanced Early Detection of Lung Cancer
Early detection of lung cancer significantly improves patient survival rates, yet traditional interpretation of chest radiographs remains challenging due to subtle abnormalities and overlapping anatomical structures. This study presents an AI-driven approach for segmenting…
Federated Deep Learning for Privacy-Preserving Early Lung Cancer Detection in Distributed Hospital Networks
Early identification is essential to increasing survival rates for lung cancer, which continues to be a significant global health concern. However, privacy issues frequently make it difficult for healthcare organizations to work together by…
Psychological Dimensions and Patient Challenges in Early Lung Cancer Detection Using AI-Based Segmentation on Chest Radiographs
Early detection of lung cancer significantly improves survival rates, yet the psychological dimensions of the diagnostic process remain underexplored. This study investigates the emotional, cognitive, and behavioral responses of patients undergoing early lung cancer…
Global Cancer Burden: A Two-Decade Analysis of Incidence, Growth, and Medical Advancements
With a sharp increase in incidence and mortality over the last 20 years, cancer has become a major global health concern. The comparative annual growth of various cancer types is highlighted, the role of…
Enhancing Precision in Lung Tumor Detection Using Transformer-Based Models on Multi-Institutional Chest Radiographs
The timely diagnosis is crucial in determining the fate of lung cancer, which remains a major cause of cancer death worldwide. Early tumor diagnosis is hampered by interpretation issues such anatomical overlap and low…
The Role of Artificial Intelligence in Healthcare: Focusing on Lung Cancer Diagnosis and Treatment
By utilizing algorithms and machine learning models, AI can process vast amounts of data, recognize patterns, and make predictions that assist healthcare professionals in making more accurate diagnoses and treatment plans. In clinical settings,…
Empowering Rural Women: Enhancing Lung Cancer Awareness and Early Detection in Underserved Communities
Lung cancer is a major public health issue worldwide, and its early detection remains crucial for increasing survival rates. However, rural women are often at a disadvantage when it comes to both awareness and…
Leveraging Artificial Intelligence in Supply Chain Management for Early Detection and Eradication of Lung Cancer
The integration of artificial intelligence (AI) into supply chain management (SCM) has revolutionized healthcare logistics, particularly in the early detection and eradication of lung cancer. AI-driven technologies such as machine learning (ML), deep learning,…
Radiographic Features and Deep Learning Approaches in the Detection and Classification of Non-Small Cell and Small Cell Lung Cancer
Lung cancer, including both Non-Small Cell Lung Cancer (NSCLC) and Small Cell Lung Cancer (SCLC), presents with diverse radiographic features that are crucial for accurate detection and classification. NSCLC includes subtypes such as adenocarcinoma,…
Detection of Lung Cancer Using AI Technology: A Comprehensive Approach
Lung cancer remains one of the leading causes of mortality worldwide. Early detection is crucial for improving patient survival rates. Artificial Intelligence (AI) has emerged as a powerful tool in the medical field, enhancing…
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