Cargando…
LungNet22: A Fine-Tuned Model for Multiclass Classification and Prediction of Lung Disease Using X-ray Images
In recent years, lung disease has increased manyfold, causing millions of casualties annually. To combat the crisis, an efficient, reliable, and affordable lung disease diagnosis technique has become indispensable. In this study, a multiclass classification of lung disease from frontal chest X-ray i...
Autores principales: | Shamrat, F. M. Javed Mehedi, Azam, Sami, Karim, Asif, Islam, Rakibul, Tasnim, Zarrin, Ghosh, Pronab, De Boer, Friso |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143659/ https://www.ncbi.nlm.nih.gov/pubmed/35629103 http://dx.doi.org/10.3390/jpm12050680 |
Ejemplares similares
-
BreastNet18: A High Accuracy Fine-Tuned VGG16 Model Evaluated Using Ablation Study for Diagnosing Breast Cancer from Enhanced Mammography Images
por: Montaha, Sidratul, et al.
Publicado: (2021) -
SkinNet-16: A deep learning approach to identify benign and malignant skin lesions
por: Ghosh, Pronab, et al.
Publicado: (2022) -
COVID-19 Detection Using Deep Learning Algorithm on Chest X-ray Images
por: Akter, Shamima, et al.
Publicado: (2021) -
Automated Detection of Broncho-Arterial Pairs Using CT Scans Employing Different Approaches to Classify Lung Diseases
por: Azam, Sami, et al.
Publicado: (2023) -
An Automated Broncho-Arterial (BA) Pair Segmentation Process and Assessment of BA Ratios in Children with Bronchiectasis Using Lung HRCT Scans: A Pilot Study
por: Azam, Sami, et al.
Publicado: (2023)