Scholarlink

The chronic respiratory diseases, including Chronic Obstructive Pulmonary Disease (COPD), Cystic Fibrosis, Chronic Bronchitis, Interstitial Lung Disease (ILD), Pleural Effusion, Pneumothorax, and Mesothelioma contribute significantly to global mortality and morbidity. The lung diseases in India are influenced by various demographic, environmental, and lifestyle factors like air pollution, high smoking rates, climate change and weather patterns, genetic, and hereditary factors. This paper highlights the current scenario of various lung diseases affecting Indian population, highest incident being of COPD to the extent of 89%. The study in this paper surveys the comparison of detection of different lung diseases using machine learning in an Indian Scenario with respect to different parameters like diseases predicted, dataset used, source of dataset, findings, limitations, future score, methods used, and accuracy. Based on the comparative study, this paper also highlights various research gaps for future scope in an Indian Scenario. By prioritizing the solutions to the identified research gaps, medical practitioners would be able to handle better India’s high respiratory disease burden, increasing the likelihood of more dependable and inclusive healthcare solutions.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Survey on the Lung Diseases Prediction in an Indian Environment Using Machine Learning

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Indushree Shetty,
  • Prerna Agrawal,
  • Savita Gandhi

摘要

The chronic respiratory diseases, including Chronic Obstructive Pulmonary Disease (COPD), Cystic Fibrosis, Chronic Bronchitis, Interstitial Lung Disease (ILD), Pleural Effusion, Pneumothorax, and Mesothelioma contribute significantly to global mortality and morbidity. The lung diseases in India are influenced by various demographic, environmental, and lifestyle factors like air pollution, high smoking rates, climate change and weather patterns, genetic, and hereditary factors. This paper highlights the current scenario of various lung diseases affecting Indian population, highest incident being of COPD to the extent of 89%. The study in this paper surveys the comparison of detection of different lung diseases using machine learning in an Indian Scenario with respect to different parameters like diseases predicted, dataset used, source of dataset, findings, limitations, future score, methods used, and accuracy. Based on the comparative study, this paper also highlights various research gaps for future scope in an Indian Scenario. By prioritizing the solutions to the identified research gaps, medical practitioners would be able to handle better India’s high respiratory disease burden, increasing the likelihood of more dependable and inclusive healthcare solutions.