Accelerating Lung Disease Diagnosis: The Role of Federated Learning and CNN in Multi-Institutional Collaboration

V Jindal, V Kukreja, DP Singh, S Vats… - … on Intelligent Systems …, 2023 - ieeexplore.ieee.org
This research employs federated learning using Convolutional Neural Networks (CNN)
across multi-institutional datasets to classify the severity of lung disease. The project …

Effectiveness of CNN Architectures and SMOTE to Overcome Imbalanced X-Ray Data in Childhood Pneumonia Detection

Y Pamungkas, MRN Ramadani… - Journal of Robotics and …, 2024 - journal.umy.ac.id
Pneumonia is a disease that causes high mortality worldwide in children and adults.
Pneumonia is caused by swelling of the lungs, and to ensure that the lungs are swollen, a …

Cn2a-capsnet: a capsule network and CNN-attention based method for COVID-19 chest X-ray image diagnosis

H Zhang, Z Lv, S Liu, Z Sang, Z Zhang - Discover Applied Sciences, 2024 - Springer
Due to its high infectivity, COVID-19 has rapidly spread worldwide, emerging as one of the
most severe and urgent diseases faced by the global community in recent years. Currently …

[PDF][PDF] Chest Radiograph Interpretation with Deep Learning

M Ahmad - 2024 - uhra.herts.ac.uk
Chest radiographs are one of the most commonly used diagnostic modalities in healthcare
due to their effectiveness in detecting conditions related to the thoracic region. However, the …

[PDF][PDF] Smoker Status Prediction Using Long Short

HF Mau - Jurnal Teknik Informatika - researchgate.net
This abstract explores the utilization of the Long Short-Term Memory (LSTM) algorithm to
predict smoking status using the Kaggle dataset consisting of 23 attributes and nearly …