[HTML][HTML] Pneumonia classification from X-ray images with inception-V3 and convolutional neural network

M Mujahid, F Rustam, R Álvarez, J Luis Vidal Mazón… - Diagnostics, 2022 - mdpi.com
Pneumonia is one of the leading causes of death in both infants and elderly people, with
approximately 4 million deaths each year. It may be a virus, bacterial, or fungal, depending …

[HTML][HTML] Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis

Q Pei, Y Luo, Y Chen, J Li, D Xie, T Ye - Clinical Chemistry and …, 2022 - degruyter.com
Artificial intelligence (AI) is a branch of computer science that includes research in robotics,
language recognition, image recognition, natural language processing, and expert systems …

[HTML][HTML] Scope of machine learning in materials research—A review

MH Mobarak, MA Mimona, MA Islam, N Hossain… - Applied Surface Science …, 2023 - Elsevier
This comprehensive review investigates the multifaceted applications of machine learning in
materials research across six key dimensions, redefining the field's boundaries. It explains …

[HTML][HTML] Deep learning for medical image-based cancer diagnosis

X Jiang, Z Hu, S Wang, Y Zhang - Cancers, 2023 - mdpi.com
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Reinforcement learning in medical image analysis: Concepts, applications, challenges, and future directions

M Hu, J Zhang, L Matkovic, T Liu… - Journal of Applied …, 2023 - Wiley Online Library
Motivation Medical image analysis involves a series of tasks used to assist physicians in
qualitative and quantitative analyses of lesions or anatomical structures which can …

Magnetic resonance imaging versus computed tomography for Three‐Dimensional bone imaging of musculoskeletal pathologies: a review

MC Florkow, K Willemsen… - Journal of Magnetic …, 2022 - Wiley Online Library
Magnetic resonance imaging (MRI) is increasingly utilized as a radiation‐free alternative to
computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal …

[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis

S Dayarathna, KT Islam, S Uribe, G Yang, M Hayat… - Medical Image …, 2023 - Elsevier
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

[HTML][HTML] Quality assurance for AI-based applications in radiation therapy

M Claessens, CS Oria, CL Brouwer, BP Ziemer… - Seminars in radiation …, 2022 - Elsevier
Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT)
and their integration into modern software-based systems raise new challenges to the …

A review on AI in PET imaging

K Matsubara, M Ibaraki, M Nemoto, H Watabe… - Annals of Nuclear …, 2022 - Springer
Artificial intelligence (AI) has been applied to various medical imaging tasks, such as
computer-aided diagnosis. Specifically, deep learning techniques such as convolutional …

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology

C Wu, G Lorenzo, DA Hormuth, EABF Lima… - Biophysics …, 2022 - pubs.aip.org
Digital twins employ mathematical and computational models to virtually represent a
physical object (eg, planes and human organs), predict the behavior of the object, and …