Algorithmic fairness in artificial intelligence for medicine and healthcare

RJ Chen, JJ Wang, DFK Williamson, TY Chen… - Nature biomedical …, 2023 - nature.com
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 …

Transformers in medical imaging: A survey

F Shamshad, S Khan, SW Zamir, MH Khan… - Medical Image …, 2023 - Elsevier
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Federated learning for smart healthcare: A survey

DC Nguyen, QV Pham, PN Pathirana, M Ding… - ACM Computing …, 2022 - dl.acm.org
Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …

Heterogeneous federated learning: State-of-the-art and research challenges

M Ye, X Fang, B Du, PC Yuen, D Tao - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …

Federated learning and differential privacy for medical image analysis

M Adnan, S Kalra, JC Cresswell, GW Taylor… - Scientific reports, 2022 - nature.com
The artificial intelligence revolution has been spurred forward by the availability of large-
scale datasets. In contrast, the paucity of large-scale medical datasets hinders the …

The role of artificial intelligence in early cancer diagnosis

B Hunter, S Hindocha, RW Lee - Cancers, 2022 - mdpi.com
Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …

Federated benchmarking of medical artificial intelligence with MedPerf

A Karargyris, R Umeton, MJ Sheller… - Nature machine …, 2023 - nature.com
Medical artificial intelligence (AI) has tremendous potential to advance healthcare by
supporting and contributing to the evidence-based practice of medicine, personalizing …

Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues

A Rahman, MS Hossain, G Muhammad, D Kundu… - Cluster computing, 2023 - Springer
Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …

Lead federated neuromorphic learning for wireless edge artificial intelligence

H Yang, KY Lam, L Xiao, Z Xiong, H Hu… - Nature …, 2022 - nature.com
In order to realize the full potential of wireless edge artificial intelligence (AI), very large and
diverse datasets will often be required for energy-demanding model training on resource …

A survey on federated learning systems: Vision, hype and reality for data privacy and protection

Q Li, Z Wen, Z Wu, S Hu, N Wang, Y Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
As data privacy increasingly becomes a critical societal concern, federated learning has
been a hot research topic in enabling the collaborative training of machine learning models …