Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging
This article is a comprehensive review of the basic background, technique, and clinical
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …
Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a scoping review
C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) is a field of computer science that deals with the simulation of
human intelligence using machines so that such machines gain problem-solving and …
human intelligence using machines so that such machines gain problem-solving and …
Advancements in oncology with artificial intelligence—a review article
Simple Summary With the advancement of artificial intelligence, including machine learning,
the field of oncology has seen promising results in cancer detection and classification …
the field of oncology has seen promising results in cancer detection and classification …
Large language models in neurology research and future practice
Recent advancements in generative artificial intelligence, particularly using large language
models (LLMs), are gaining increased public attention. We provide a perspective on the …
models (LLMs), are gaining increased public attention. We provide a perspective on the …
Artificial intelligence and deep learning in neuroradiology: exploring the new frontier
H Kaka, E Zhang, N Khan - Canadian Association of …, 2021 - journals.sagepub.com
There have been many recently published studies exploring machine learning (ML) and
deep learning applications within neuroradiology. The improvement in performance of these …
deep learning applications within neuroradiology. The improvement in performance of these …
Topics and trends in artificial intelligence assisted human brain research
Artificial intelligence (AI) assisted human brain research is a dynamic interdisciplinary field
with great interest, rich literature, and huge diversity. The diversity in research topics and …
with great interest, rich literature, and huge diversity. The diversity in research topics and …
Using adversarial images to assess the robustness of deep learning models trained on diagnostic images in oncology
PURPOSE Deep learning (DL) models have rapidly become a popular and cost-effective
tool for image classification within oncology. A major limitation of DL models is their …
tool for image classification within oncology. A major limitation of DL models is their …
Machine learning using multiparametric magnetic resonance imaging radiomic feature analysis to predict Ki-67 in World Health Organization grade I meningiomas
O Khanna, AF Kazerooni, CJ Farrell… - …, 2021 - journals.lww.com
BACKGROUND Although World Health Organization (WHO) grade I meningiomas are
considered “benign” tumors, an elevated Ki-67 is one crucial factor that has been shown to …
considered “benign” tumors, an elevated Ki-67 is one crucial factor that has been shown to …
Application of artificial intelligence methods for imaging of spinal metastasis
Simple Summary Spinal metastasis is the most common malignant disease of the spine, and
its early diagnosis and treatment is important to prevent complications and improve quality of …
its early diagnosis and treatment is important to prevent complications and improve quality of …
Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response
N Vladimirov, O Perlman - International Journal of Molecular Sciences, 2023 - mdpi.com
Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several
indications has yielded improved prognosis for cases where traditional therapy has shown …
indications has yielded improved prognosis for cases where traditional therapy has shown …