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 …
Explainable AI (XAI): Core ideas, techniques, and solutions
As our dependence on intelligent machines continues to grow, so does the demand for more
transparent and interpretable models. In addition, the ability to explain the model generally …
transparent and interpretable models. In addition, the ability to explain the model generally …
[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 …
Unlocking the value of artificial intelligence in human resource management through AI capability framework
Artificial Intelligence (AI) is increasingly adopted within Human Resource management
(HRM) due to its potential to create value for consumers, employees, and organisations …
(HRM) due to its potential to create value for consumers, employees, and organisations …
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 …
Six human-centered artificial intelligence grand challenges
Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the
human condition in ways that are not yet well understood. Negative unintended …
human condition in ways that are not yet well understood. Negative unintended …
[HTML][HTML] Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost
Z Li - Computers, Environment and Urban Systems, 2022 - Elsevier
Abstract Machine learning and artificial intelligence (ML/AI), previously considered black box
approaches, are becoming more interpretable, as a result of the recent advances in …
approaches, are becoming more interpretable, as a result of the recent advances in …
Language in a bottle: Language model guided concept bottlenecks for interpretable image classification
Abstract Concept Bottleneck Models (CBM) are inherently interpretable models that factor
model decisions into human-readable concepts. They allow people to easily understand …
model decisions into human-readable concepts. They allow people to easily understand …
A systematic review of explainable artificial intelligence in terms of different application domains and tasks
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved
and are now being employed in almost every application domain to develop automated or …
and are now being employed in almost every application domain to develop automated or …
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 …