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 …
Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …
symptoms that appear in early childhood. ASD is also associated with communication …
Technological paradoxes and artificial intelligence implementation in healthcare. An application of paradox theory
AI is transforming healthcare system with many innovations in diagnosis, drug research and
advancement in medical treatments. But there are several concerns and dilemmas related to …
advancement in medical treatments. But there are several concerns and dilemmas related to …
[HTML][HTML] Quality assurance for AI-based applications in radiation therapy
Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT)
and their integration into modern software-based systems raise new challenges to the …
and their integration into modern software-based systems raise new challenges to the …
[HTML][HTML] Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples
L Ubaldi, V Valenti, RF Borgese, G Collura… - Physica Medica, 2021 - Elsevier
Predictive models based on radiomics and machine-learning (ML) need large and
annotated datasets for training, often difficult to collect. We designed an operative pipeline …
annotated datasets for training, often difficult to collect. We designed an operative pipeline …
AI and machine learning ethics, law, diversity, and global impact
K Drabiak, S Kyzer, V Nemov… - The British journal of …, 2023 - academic.oup.com
Artificial intelligence (AI) and its machine learning (ML) algorithms are offering new promise
for personalized biomedicine and more cost-effective healthcare with impressive technical …
for personalized biomedicine and more cost-effective healthcare with impressive technical …
[HTML][HTML] Evaluation of trustworthy artificial intelligent healthcare applications using multi-criteria decision-making approach
The purpose of this paper is to propose a novel hybrid framework for evaluating and
benchmarking trustworthy artificial intelligence (AI) applications in healthcare by using multi …
benchmarking trustworthy artificial intelligence (AI) applications in healthcare by using multi …
Prediction of preeclampsia using machine learning and deep learning models: a review
SS Aljameel, M Alzahrani, R Almusharraf… - Big Data and Cognitive …, 2023 - mdpi.com
Preeclampsia is one of the illnesses associated with placental dysfunction and pregnancy-
induced hypertension, which appears after the first 20 weeks of pregnancy and is marked by …
induced hypertension, which appears after the first 20 weeks of pregnancy and is marked by …
Alzheimer's Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …
approaches. This systematic review surveys the recent literature (2018 onwards) to …
The role of AI in hospitals and clinics: transforming healthcare in the 21st century
S Maleki Varnosfaderani, M Forouzanfar - Bioengineering, 2024 - mdpi.com
As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …