[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 …

A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance

A Masood, K Ahmad - Journal of Cleaner Production, 2021 - Elsevier
Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …

[HTML][HTML] Artificial intelligence for COVID-19: a systematic review

L Wang, Y Zhang, D Wang, X Tong, T Liu… - Frontiers in …, 2021 - frontiersin.org
Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute
respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead …

Clinically applicable artificial intelligence system for dental diagnosis with CBCT

M Ezhov, M Gusarev, M Golitsyna, JM Yates… - Scientific reports, 2021 - nature.com
In this study, a novel AI system based on deep learning methods was evaluated to
determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks …

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 …

Artificial intelligence in orthodontics: Evaluation of a fully automated cephalometric analysis using a customized convolutional neural network.

F Kunz, A Stellzig-Eisenhauer… - Journal of Orofacial …, 2020 - search.ebscohost.com
Purpose The aim of this investigation was to create an automated cephalometric X-ray
analysis using a specialized artificial intelligence (AI) algorithm. We compared the accuracy …

Comparing LSTM and GRU models to predict the condition of a pulp paper press

BC Mateus, M Mendes, JT Farinha, R Assis… - Energies, 2021 - mdpi.com
The accuracy of a predictive system is critical for predictive maintenance and to support the
right decisions at the right times. Statistical models, such as ARIMA and SARIMA, are unable …

Radiomics, machine learning, and artificial intelligence—what the neuroradiologist needs to know

MW Wagner, K Namdar, A Biswas, S Monah, F Khalvati… - Neuroradiology, 2021 - Springer
Purpose Artificial intelligence (AI) is playing an ever-increasing role in Neuroradiology.
Methods When designing AI-based research in neuroradiology and appreciating the …

Fairness of artificial intelligence in healthcare: review and recommendations

D Ueda, T Kakinuma, S Fujita, K Kamagata… - Japanese Journal of …, 2024 - Springer
In this review, we address the issue of fairness in the clinical integration of artificial
intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a …

The current state of artificial intelligence in ophthalmology

R Kapoor, SP Walters, LA Al-Aswad - Survey of ophthalmology, 2019 - Elsevier
Artificial intelligence (AI) is a branch of computer science that deals with the development of
algorithms that seek to simulate human intelligence. We provide an overview of the basic …