Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …
applications in healthcare, such as health services management, predictive medicine …
Artificial intelligence for multimodal data integration in oncology
In oncology, the patient state is characterized by a whole spectrum of modalities, ranging
from radiology, histology, and genomics to electronic health records. Current artificial …
from radiology, histology, and genomics to electronic health records. Current artificial …
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 …
Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning
Cancer is a fatal disease caused by a combination of genetic diseases and a variety of
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
A review on explainable artificial intelligence for healthcare: why, how, and when?
S Bharati, MRH Mondal… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …
medicine. Concerns have been raised about the explainability of the decisions that are …
DeepXplainer: An interpretable deep learning based approach for lung cancer detection using explainable artificial intelligence
Abstract Background and Objective Artificial intelligence (AI) has several uses in the
healthcare industry, some of which include healthcare management, medical forecasting …
healthcare industry, some of which include healthcare management, medical forecasting …
Hyperspectral image classification: Potentials, challenges, and future directions
Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …
imagery and remote sensing. The current intelligent technologies, such as support vector …
Lung cancer prediction model using ensemble learning techniques and a systematic review analysis
Lung cancers are malignant lung tumors resulting from uncontrolled growth of lung cells that
metastasizes to other parts of the body and can cause death. Although lung cancer cannot …
metastasizes to other parts of the body and can cause death. Although lung cancer cannot …
The inadequacy of Shapley values for explainability
X Huang, J Marques-Silva - arXiv preprint arXiv:2302.08160, 2023 - arxiv.org
This paper develops a rigorous argument for why the use of Shapley values in explainable
AI (XAI) will necessarily yield provably misleading information about the relative importance …
AI (XAI) will necessarily yield provably misleading information about the relative importance …
Harnessing fusion modeling for enhanced breast cancer classification through interpretable artificial intelligence and in-depth explanations
Abstract Integrating Artificial Intelligence (AI) into healthcare has shown tremendous promise
in several domains, such as prediction, decision-making, and diagnosis. Nevertheless, the …
in several domains, such as prediction, decision-making, and diagnosis. Nevertheless, the …