Regulatory aspects of the use of artificial intelligence medical software

F Zanca, C Brusasco, F Pesapane, Z Kwade… - Seminars in radiation …, 2022 - Elsevier
The rapidly evolving scenario of Artificial intelligence (AI) in medicine comes with new
regulatory challenges, including certification, ownership, and control of data sharing, privacy …

Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model …

A Barragán-Montero, A Bibal… - Physics in Medicine …, 2022 - iopscience.iop.org
The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …

Deep embedded median clustering for routing misbehaviour and attacks detection in ad-hoc networks

A Rajendran, N Balakrishnan, P Ajay - Ad Hoc Networks, 2022 - Elsevier
Due to the properties of ad-hoc networks, it appears that designing sophisticated defence
schemes with more computing capital is impossible in most situations. Recently, an …

[HTML][HTML] Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools

O Diaz, K Kushibar, R Osuala, A Linardos, L Garrucho… - Physica medica, 2021 - Elsevier
The vast amount of data produced by today's medical imaging systems has led medical
professionals to turn to novel technologies in order to efficiently handle their data and exploit …

Automation and artificial intelligence in radiation therapy treatment planning

S Jones, K Thompson, B Porter… - Journal of Medical …, 2024 - Wiley Online Library
Automation and artificial intelligence (AI) is already possible for many radiation therapy
planning and treatment processes with the aim of improving workflows and increasing …

Recent applications of artificial intelligence in radiotherapy: where we are and beyond

M Santoro, S Strolin, G Paolani, G Della Gala… - Applied Sciences, 2022 - mdpi.com
Featured Application Computational models based on artificial intelligence (AI) variants
have been developed and applied successfully in many areas, both inside and outside of …

[PDF][PDF] Deep learning techniques for COVID-19 detection based on chest X-ray and CT-scan images: a short review and future perspective

MM Mijwil, K Aggarwal, R Doshi, KK Hiran… - Asian J Appl …, 2022 - researchgate.net
Today, humans live in the era of rapid growth in electronic devices that are based on
artificial intelligence, including the significant growth in the manufacture of machines that …

Treatment plan prediction for lung IMRT using deep learning based fluence map generation

L Vandewinckele, S Willems, M Lambrecht, P Berkovic… - Physica Medica, 2022 - Elsevier
Purpose Recently, it has been shown that automated treatment planning can be executed by
direct fluence prediction from patient anatomy using convolutional neural networks. Proof of …

Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow

P Meyer, MC Biston, C Khamphan, T Marghani… - Cancer …, 2021 - Elsevier
Modern radiotherapy treatment planning is a complex and time-consuming process that
requires the skills of experienced users to obtain quality plans. Since the early 2000s, the …

Big data for biomedical education with a focus on the COVID-19 era: an integrative review of the literature

R Khamisy-Farah, P Gilbey, LB Furstenau… - International Journal of …, 2021 - mdpi.com
Medical education refers to education and training delivered to medical students in order to
become a practitioner. In recent decades, medicine has been radically transformed by …