Multimodal federated learning: A survey
Federated learning (FL), which provides a collaborative training scheme for distributed data
sources with privacy concerns, has become a burgeoning and attractive research area. Most …
sources with privacy concerns, has become a burgeoning and attractive research area. Most …
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 …
Federated learning on multimodal data: A comprehensive survey
With the growing awareness of data privacy, federated learning (FL) has gained increasing
attention in recent years as a major paradigm for training models with privacy protection in …
attention in recent years as a major paradigm for training models with privacy protection in …
Symmetry in privacy-based healthcare: a review of skin cancer detection and classification using federated learning
Skin cancer represents one of the most lethal and prevalent types of cancer observed in the
human population. When diagnosed in its early stages, melanoma, a form of skin cancer …
human population. When diagnosed in its early stages, melanoma, a form of skin cancer …
Federated learning for decentralized artificial intelligence in melanoma diagnostics
S Haggenmüller, M Schmitt… - JAMA …, 2024 - jamanetwork.com
Importance The development of artificial intelligence (AI)–based melanoma classifiers
typically calls for large, centralized datasets, requiring hospitals to give away their patient …
typically calls for large, centralized datasets, requiring hospitals to give away their patient …
Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation
In healthcare, machine learning (ML) shows significant potential to augment patient care,
improve population health, and streamline healthcare workflows. Realizing its full potential …
improve population health, and streamline healthcare workflows. Realizing its full potential …
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 …
Federated and Transfer Learning Methods for the Classification of Melanoma and Nonmelanoma Skin Cancers: A Prospective Study
Skin cancer is considered a dangerous type of cancer with a high global mortality rate.
Manual skin cancer diagnosis is a challenging and time-consuming method due to the …
Manual skin cancer diagnosis is a challenging and time-consuming method due to the …
Applications and challenges of federated learning paradigm in the big data era with special emphasis on COVID-19
A Majeed, X Zhang, SO Hwang - Big Data and Cognitive Computing, 2022 - mdpi.com
Federated learning (FL) is one of the leading paradigms of modern times with higher privacy
guarantees than any other digital solution. Since its inception in 2016, FL has been …
guarantees than any other digital solution. Since its inception in 2016, FL has been …
A federated learning system with data fusion for healthcare using multi-party computation and additive secret sharing
In the Internet of medical things, data from a single source can be easily analyzed. Besides,
it is paramount to collect data from multiple sources to provide consistent, accurate, and vital …
it is paramount to collect data from multiple sources to provide consistent, accurate, and vital …