Year: 2025
Type: article
Abstract: Respiratory illnesses continue to seriously impact global health. Since the 2020 outbreak, death rates for those with lung conditions have alarmingly climbed. Early diagnoses prove crucial to promptly treating patients and bettering outcomes. Traditional testing frequently necessitates too much time before results, delaying vital interventions.Advances in computer vision, deep learning algorithms, and openly accessible datasets now allow integrating artificial intelligence in medical diagnoses. Machine learning models have dramatically cut detection times and lessened manual review in lung disease identification.This investigation explores applying various machine learning algorithms for diagnosing different lung diseases. The primary aim is to analyze developing patterns in AI- assisted lung condition detection, recognize current barriers, and envision future opportunities in this area. Improving accuracy and broadening the scope of machine learning-aided lung disease identification can pave the way for more efficient and accessible healthcare solutions. Keywords- Image Classification, Medical Diagnoses, Convolutional Neural Networks, COVID-19, Lung Disease Detection.
DOI: 10.55041/ijsrem43887
Authors: P .SaiTeja, M .Kalyan, P.Bhuvan Kumar
Language: English
Topic: COVID-19 diagnosis using AI
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4409245828