Collaborative federated learning for healthcare: Multi-modal covid-19 diagnosis at the edge
Despite significant improvements over the last few years, cloud-based healthcare
applications continue to suffer from poor adoption due to their limitations in meeting stringent …
applications continue to suffer from poor adoption due to their limitations in meeting stringent …
Federated learning for COVID-19 screening from Chest X-ray images
Today, the whole world is facing a great medical disaster that affects the health and lives of
the people: the COVID-19 disease, colloquially known as the Corona virus. Deep learning is …
the people: the COVID-19 disease, colloquially known as the Corona virus. Deep learning is …
Dynamic-fusion-based federated learning for COVID-19 detection
Medical diagnostic image analysis (eg, CT scan or X-Ray) using machine learning is an
efficient and accurate way to detect COVID-19 infections. However, the sharing of diagnostic …
efficient and accurate way to detect COVID-19 infections. However, the sharing of diagnostic …
Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions
With the advent of the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning
(ML), and Deep Learning (DL) algorithms, the landscape of data-driven medical applications …
(ML), and Deep Learning (DL) algorithms, the landscape of data-driven medical applications …
Flop: Federated learning on medical datasets using partial networks
The outbreak of COVID-19 Disease due to the novel coronavirus has caused a shortage of
medical resources. To aid and accelerate the diagnosis process, automatic diagnosis of …
medical resources. To aid and accelerate the diagnosis process, automatic diagnosis of …
A comprehensive review of federated learning for COVID‐19 detection
Abstract The coronavirus of 2019 (COVID‐19) was declared a global pandemic by World
Health Organization in March 2020. Effective testing is crucial to slow the spread of the …
Health Organization in March 2020. Effective testing is crucial to slow the spread of the …
Federated learning for healthcare domain-pipeline, applications and challenges
M Joshi, A Pal, M Sankarasubbu - ACM Transactions on Computing for …, 2022 - dl.acm.org
Federated learning is the process of developing machine learning models over datasets
distributed across data centers such as hospitals, clinical research labs, and mobile devices …
distributed across data centers such as hospitals, clinical research labs, and mobile devices …
Experiments of federated learning for covid-19 chest x-ray images
AI plays an important role in COVID-19 identification. Computer vision and deep learning
techniques can assist in determining COVID-19 infection with Chest X-ray Images. However …
techniques can assist in determining COVID-19 infection with Chest X-ray Images. However …
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence
Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses;
however, concerns surrounding security and trustworthiness impede the collection of large …
however, concerns surrounding security and trustworthiness impede the collection of large …
Federated learning for smart healthcare: A survey
Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …