Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
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 …
Federated learning for healthcare: Systematic review and architecture proposal
The use of machine learning (ML) with electronic health records (EHR) is growing in
popularity as a means to extract knowledge that can improve the decision-making process in …
popularity as a means to extract knowledge that can improve the decision-making process in …
Federated learning enables big data for rare cancer boundary detection
Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but …
generalizability is concerning. This is currently addressed by sharing multi-site data, but …
[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
Deep learning and medical image analysis for COVID-19 diagnosis and prediction
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
Federated learning for predicting clinical outcomes in patients with COVID-19
Federated learning (FL) is a method used for training artificial intelligence models with data
from multiple sources while maintaining data anonymity, thus removing many barriers to …
from multiple sources while maintaining data anonymity, thus removing many barriers to …
Review on security of federated learning and its application in healthcare
Artificial intelligence (AI) has led to a high rate of development in healthcare, and good
progress has been made on many complex medical problems. However, there is a lack of …
progress has been made on many complex medical problems. However, there is a lack of …
[HTML][HTML] PDAtt-Unet: Pyramid dual-decoder attention Unet for Covid-19 infection segmentation from CT-scans
Since the emergence of the Covid-19 pandemic in late 2019, medical imaging has been
widely used to analyze this disease. Indeed, CT-scans of the lungs can help diagnose …
widely used to analyze this disease. Indeed, CT-scans of the lungs can help diagnose …
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 …