Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
M Arabahmadi, R Farahbakhsh, J Rezazadeh - Sensors, 2022 - mdpi.com
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …
use of technology in medicine has made significant contributions to human society. In this …
Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
As far back as the industrial revolution, significant development in technical innovation has
succeeded in transforming numerous manual tasks and processes that had been in …
succeeded in transforming numerous manual tasks and processes that had been in …
[HTML][HTML] Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence
Medical artificial intelligence (AI) systems have been remarkably successful, even
outperforming human performance at certain tasks. There is no doubt that AI is important to …
outperforming human performance at certain tasks. There is no doubt that AI is important to …
[HTML][HTML] An overview of deep learning in medical imaging focusing on MRI
AS Lundervold, A Lundervold - Zeitschrift für Medizinische Physik, 2019 - Elsevier
What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
Effectiveness of COVID-19 diagnosis and management tools: A review
W Alsharif, A Qurashi - Radiography, 2021 - Elsevier
Objective To review the available literature concerning the effectiveness of the COVID-19
diagnostic tools. Background With the absence of specific treatment/vaccines for the …
diagnostic tools. Background With the absence of specific treatment/vaccines for the …
Federated learning for predicting clinical outcomes in patients with COVID-19
Federated learning (FL) is a method used for training artificial intelligence models with data
from multiple sources while maintaining data anonymity, thus removing many barriers to …
from multiple sources while maintaining data anonymity, thus removing many barriers to …
Artificial intelligence in anesthesiology: current techniques, clinical applications, and limitations
Artificial intelligence has been advancing in fields including anesthesiology. This scoping
review of the intersection of artificial intelligence and anesthesia research identified and …
review of the intersection of artificial intelligence and anesthesia research identified and …
Domain wall memory: Physics, materials, and devices
Digital data, generated by corporate and individual users, is growing day by day due to a
vast range of digital applications. Magnetic hard disk drives (HDDs) currently fulfill the …
vast range of digital applications. Magnetic hard disk drives (HDDs) currently fulfill the …
Machine learning and deep learning in medical imaging: intelligent imaging
Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An
understanding of the principles and application of radiomics, artificial neural networks …
understanding of the principles and application of radiomics, artificial neural networks …
Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)
Objective There has been a large amount of research in the field of artificial intelligence (AI)
as applied to clinical radiology. However, these studies vary in design and quality and …
as applied to clinical radiology. However, these studies vary in design and quality and …