Ethical framework for Artificial Intelligence and Digital technologies
Abstract The use of Artificial Intelligence (AI) in Digital technologies (DT) is proliferating a
profound socio-technical transformation. Governments and AI scholarship have endorsed …
profound socio-technical transformation. Governments and AI scholarship have endorsed …
AI applications to medical images: From machine learning to deep learning
Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …
research and healthcare services. This review focuses on challenges points to be clarified …
Navigating the pitfalls of applying machine learning in genomics
The scale of genetic, epigenomic, transcriptomic, cheminformatic and proteomic data
available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the …
available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the …
Interactive and explainable region-guided radiology report generation
The automatic generation of radiology reports has the potential to assist radiologists in the
time-consuming task of report writing. Existing methods generate the full report from image …
time-consuming task of report writing. Existing methods generate the full report from image …
Deep learning for tomographic image reconstruction
Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
Checklist for artificial intelligence in medical imaging (CLAIM): a guide for authors and reviewers
Study Design Item 5. Indicate if the study is retrospective or prospective. Evaluate predictive
models in a prospective setting, if possible. Item 6. Define the study's goal, such as model …
models in a prospective setting, if possible. Item 6. Define the study's goal, such as model …
On the interpretability of artificial intelligence in radiology: challenges and opportunities
As artificial intelligence (AI) systems begin to make their way into clinical radiology practice,
it is crucial to assure that they function correctly and that they gain the trust of experts …
it is crucial to assure that they function correctly and that they gain the trust of experts …
[HTML][HTML] Deep learning and medical image analysis for COVID-19 diagnosis and prediction
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
On interpretability of artificial neural networks: A survey
Deep learning as performed by artificial deep neural networks (DNNs) has achieved great
successes recently in many important areas that deal with text, images, videos, graphs, and …
successes recently in many important areas that deal with text, images, videos, graphs, and …