A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion
In the last few years, the trend in health care of embracing artificial intelligence (AI) has
dramatically changed the medical landscape. Medical centres have adopted AI applications …
dramatically changed the medical landscape. Medical centres have adopted AI applications …
Remote patient monitoring using artificial intelligence: Current state, applications, and challenges
The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
Survey of explainable AI techniques in healthcare
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
[HTML][HTML] Transparency of deep neural networks for medical image analysis: A review of interpretability methods
Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
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 …
Multimodal machine learning in precision health: A scoping review
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …
sector including utilization for clinical decision-support. Its use has historically been focused …
[HTML][HTML] Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …
[HTML][HTML] Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks
Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …
diagnosis with their outstanding image classification performance. In spite of the outstanding …
Image segmentation for MR brain tumor detection using machine learning: a review
Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
disease and monitor treatment as non-invasive imaging technology. MRI produces three …