Transformers in medical imaging: A survey
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …
successfully applied to several computer vision problems, achieving state-of-the-art results …
Explainable AI for healthcare 5.0: opportunities and challenges
D Saraswat, P Bhattacharya, A Verma, VK Prasad… - IEEE …, 2022 - ieeexplore.ieee.org
In the healthcare domain, a transformative shift is envisioned towards Healthcare 5.0. It
expands the operational boundaries of Healthcare 4.0 and leverages patient-centric digital …
expands the operational boundaries of Healthcare 4.0 and leverages patient-centric digital …
[HTML][HTML] Significance of machine learning in healthcare: Features, pillars and applications
Abstract Machine Learning (ML) applications are making a considerable impact on
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
[HTML][HTML] Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities
The past decade has seen significant progress in artificial intelligence (AI), which has
resulted in algorithms being adopted for resolving a variety of problems. However, this …
resulted in algorithms being adopted for resolving a variety of problems. However, this …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Privacy and artificial intelligence: challenges for protecting health information in a new era
B Murdoch - BMC Medical Ethics, 2021 - Springer
Background Advances in healthcare artificial intelligence (AI) are occurring rapidly and there
is a growing discussion about managing its development. Many AI technologies end up …
is a growing discussion about managing its development. Many AI technologies end up …
Natural resources, green innovation, fintech, and sustainability: A fresh insight from BRICS
Since the industrial revolution, the financial sector has become a significant claimant toward
the growth of human society. However, supporting the adverse environmental projects in …
the growth of human society. However, supporting the adverse environmental projects in …
[HTML][HTML] A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations …
Abstract Machine learning (ML) techniques are often employed for the accurate prediction of
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …
[HTML][HTML] The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and …
Artificial intelligence (AI) has huge potential to improve the health and well-being of people,
but adoption in clinical practice is still limited. Lack of transparency is identified as one of the …
but adoption in clinical practice is still limited. Lack of transparency is identified as one of the …
Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …
there is a great need to deliberate on the future of the cities worth living. In particular, as …