Lung Disease Diagnosis Using Machine Learning from a Bibliometric Perspective

Lung disease detection using machine learning is an active area of research that aims to develop models that can accurately identify and diagnose lung diseases using medical imaging data, such as CT scans. These models use various machine learning techniques, such as deep learning and computer vision algorithms, to analyze the images and identify patterns that may indicate the presence of a specific disease. By using the keywords “lung disease,” “diagnosis,” and “machine learning,” on the Scopus database, 64 documents were extracted. The results showed that Canada is the world leader in this field of study, and the University of Malaya, Hohai University, and Ahsanullah University of Science and Technology were the most prolific institutions. In addition, X. Chen is the author with the most citations, at 29. This study will provide a future roadmap for the researchers to find the trends in this domain.