Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities
Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …
ageing global population to the current COVID-19 pandemic. In a world where we have …
[HTML][HTML] Convolutional neural network techniques for brain tumor classification (from 2015 to 2022): Review, challenges, and future perspectives
Y Xie, F Zaccagna, L Rundo, C Testa, R Agati, R Lodi… - Diagnostics, 2022 - mdpi.com
Convolutional neural networks (CNNs) constitute a widely used deep learning approach that
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …
[HTML][HTML] Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review
BM de Vries, GJC Zwezerijnen, GL Burchell… - Frontiers in …, 2023 - frontiersin.org
Rational Deep learning (DL) has demonstrated a remarkable performance in diagnostic
imaging for various diseases and modalities and therefore has a high potential to be used …
imaging for various diseases and modalities and therefore has a high potential to be used …
[HTML][HTML] Exploring the capabilities of a lightweight CNN model in accurately identifying renal abnormalities: Cysts, stones, and tumors, using LIME and SHAP
Kidney abnormality is one of the major concerns in modern society, and it affects millions of
people around the world. To diagnose different abnormalities in human kidneys, a narrow …
people around the world. To diagnose different abnormalities in human kidneys, a narrow …
[HTML][HTML] Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review
C Ladbury, R Zarinshenas, H Semwal… - Translational Cancer …, 2022 - ncbi.nlm.nih.gov
Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a
narrative review - PMC Back to Top Skip to main content NIH NLM Logo Access keys NCBI …
narrative review - PMC Back to Top Skip to main content NIH NLM Logo Access keys NCBI …
[HTML][HTML] Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach
COVID-19 has caused over 528 million infected cases and over 6.25 million deaths since its
outbreak in 2019. The uncontrolled transmission of the SARS-CoV-2 virus has caused …
outbreak in 2019. The uncontrolled transmission of the SARS-CoV-2 virus has caused …
[HTML][HTML] Auguring fake face images using dual input convolution neural network
Deepfake technology uses auto-encoders and generative adversarial networks to replace or
artificially construct fine-tuned faces, emotions, and sounds. Although there have been …
artificially construct fine-tuned faces, emotions, and sounds. Although there have been …
[HTML][HTML] A scoping review of interpretability and explainability concerning artificial intelligence methods in medical imaging
Abstract Purpose To review eXplainable Artificial Intelligence/(XAI) methods available for
medical imaging/(MI). Method A scoping review was conducted following the Joanna Briggs …
medical imaging/(MI). Method A scoping review was conducted following the Joanna Briggs …
[HTML][HTML] Designing optimal convolutional neural network architecture using differential evolution algorithm
Convolutional neural networks (CNNs) are deep learning models used widely for solving
various tasks like computer vision and speech recognition. CNNs are developed manually …
various tasks like computer vision and speech recognition. CNNs are developed manually …
GLIME: general, stable and local LIME explanation
As black-box machine learning models become more complex and are applied in high-
stakes settings, the need for providing explanations for their predictions becomes crucial …
stakes settings, the need for providing explanations for their predictions becomes crucial …