Reviewing federated machine learning and its use in diseases prediction
Machine learning (ML) has succeeded in improving our daily routines by enabling
automation and improved decision making in a variety of industries such as healthcare …
automation and improved decision making in a variety of industries such as healthcare …
Explainable, domain-adaptive, and federated artificial intelligence in medicine
Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in
each domain is driven by a growing body of annotated data, increased computational …
each domain is driven by a growing body of annotated data, increased computational …
Decentralized learning in healthcare: a review of emerging techniques
Recent developments in deep learning have contributed to numerous success stories in
healthcare. The performance of a deep learning model generally improves with the size of …
healthcare. The performance of a deep learning model generally improves with the size of …
Secure smart communication efficiency in federated learning: Achievements and challenges
Federated learning (FL) is known to perform machine learning tasks in a distributed manner.
Over the years, this has become an emerging technology, especially with various data …
Over the years, this has become an emerging technology, especially with various data …
DRFL: federated learning in diabetic retinopathy grading using fundus images
Diabetic retinopathy (DR) is a complication of diabetic Mellitus, develo** retinal lesions
that impair vision. The DR detection in the early stages avoids permanent vision loss. The …
that impair vision. The DR detection in the early stages avoids permanent vision loss. The …
NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image data
In the realm of precision medicine, the potential of deep learning is progressively harnessed
to facilitate intricate clinical decision-making, especially when navigating multifaceted …
to facilitate intricate clinical decision-making, especially when navigating multifaceted …
A systematic review on diabetic retinopathy detection and classification based on deep learning techniques using fundus images
Diabetic retinopathy (DR) is the leading cause of visual impairment globally. It occurs due to
long-term diabetes with fluctuating blood glucose levels. It has become a significant concern …
long-term diabetes with fluctuating blood glucose levels. It has become a significant concern …
Federated Learning for Diabetic Retinopathy Detection Using Vision Transformers
A common consequence of diabetes mellitus called diabetic retinopathy (DR) results in
lesions on the retina that impair vision. It can cause blindness if not detected in time …
lesions on the retina that impair vision. It can cause blindness if not detected in time …
[HTML][HTML] Role of federated learning in healthcare systems: A survey
Nowadays, machine learning affects practically every industry, but the effectiveness of these
systems depends on the accessibility of training data sets. Every device now produces data …
systems depends on the accessibility of training data sets. Every device now produces data …
DRSegNet: A cutting-edge approach to Diabetic Retinopathy segmentation and classification using parameter-aware Nature-Inspired optimization
Diabetic retinopathy (DR) is a prominent reason of blindness globally, which is a
diagnostically challenging disease owing to the intricate process of its development and the …
diagnostically challenging disease owing to the intricate process of its development and the …