Machine learning and deep learning: A review of methods and applications

K Sharifani, M Amini - World Information Technology and …, 2023 - papers.ssrn.com
Abstract Machine learning and deep learning have rapidly emerged as powerful tools in
many fields, including image and speech recognition, natural language processing, and …

[HTML][HTML] Artificial intelligence in diagnostic and interventional radiology: where are we now?

T Boeken, J Feydy, A Lecler, P Soyer, A Feydy… - Diagnostic and …, 2023 - Elsevier
The emergence of massively parallel yet affordable computing devices has been a game
changer for research in the field of artificial intelligence (AI). In addition, dramatic investment …

Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system

P Sharma, Z Said, A Kumar, S Nizetic, A Pandey… - Energy & …, 2022 - ACS Publications
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …

[HTML][HTML] Application of artificial intelligence technology in oncology: Towards the establishment of precision medicine

R Hamamoto, K Suvarna, M Yamada, K Kobayashi… - Cancers, 2020 - mdpi.com
Simple Summary Artificial intelligence (AI) technology has been advancing rapidly in recent
years and is being implemented in society. The medical field is no exception, and the clinical …

[HTML][HTML] Artificial intelligence in lung cancer: current applications and perspectives

G Chassagnon, C De Margerie-Mellon… - Japanese journal of …, 2023 - Springer
Artificial intelligence (AI) has been a very active research topic over the last years and
thoracic imaging has particularly benefited from the development of AI and in particular deep …

[HTML][HTML] Artificial intelligence: A critical review of applications for lung nodule and lung cancer

C de Margerie-Mellon, G Chassagnon - Diagnostic and Interventional …, 2023 - Elsevier
Artificial intelligence (AI) is a broad concept that usually refers to computer programs that
can learn from data and perform certain specific tasks. In the recent years, the growth of …

[HTML][HTML] External validation of a commercially available deep learning algorithm for fracture detection in children

M Dupuis, L Delbos, R Veil, C Adamsbaum - Diagnostic and Interventional …, 2022 - Elsevier
Purpose The purpose of this study was to conduct an external validation of a fracture
assessment deep learning algorithm (Rayvolve®) using digital radiographs from a real-life …

[HTML][HTML] Role of machine learning in precision oncology: applications in gastrointestinal cancers

A Tabari, SM Chan, OMF Omar, SI Iqbal, MS Gee… - Cancers, 2022 - mdpi.com
Simple Summary Worldwide gastrointestinal (GI) malignancies account for about 25% of the
global cancer incidence. For some malignancies, screening programs, such as routine colon …

[HTML][HTML] Comparison of two deep learning image reconstruction algorithms in chest CT images: a task-based image quality assessment on phantom data

J Greffier, J Frandon, S Si-Mohamed, D Dabli… - Diagnostic and …, 2022 - Elsevier
Purpose The purpose of this study was to compare the effect of two deep learning image
reconstruction (DLR) algorithms in chest computed tomography (CT) with different clinical …

[HTML][HTML] Artificial intelligence in emergency radiology: a review of applications and possibilities

BD Katzman, CB van der Pol, P Soyer… - … and Interventional Imaging, 2023 - Elsevier
Artificial intelligence (AI) applications in radiology have been rising exponentially in the last
decade. Although AI has found usage in various areas of healthcare, its utilization in the …