Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care

E Trivizakis, GZ Papadakis… - International …, 2020 - spandidos-publications.com
The new era of artificial intelligence (AI) has introduced revolutionary data‑driven analysis
paradigms that have led to significant advancements in information processing techniques …

Role of artificial intelligence in radiogenomics for cancers in the era of precision medicine

S Saxena, B Jena, N Gupta, S Das, D Sarmah… - Cancers, 2022 - mdpi.com
Simple Summary Recently, radiogenomics has played a significant role and offered a new
understanding of cancer's biology and behavior in response to standard therapy. It also …

The era of radiogenomics in precision medicine: an emerging approach to support diagnosis, treatment decisions, and prognostication in oncology

L Shui, H Ren, X Yang, J Li, Z Chen, C Yi, H Zhu… - Frontiers in …, 2021 - frontiersin.org
With the rapid development of new technologies, including artificial intelligence and genome
sequencing, radiogenomics has emerged as a state-of-the-art science in the field of …

Extendable and explainable deep learning for pan-cancer radiogenomics research

Q Liu, P Hu - Current opinion in chemical biology, 2022 - Elsevier
Radiogenomics is a field where medical images and genomic profiles are jointly analyzed to
answer critical clinical questions. Specifically, people want to identify non-invasive imaging …

Radiomics in radiooncology–challenging the medical physicist

JC Peeken, M Bernhofer, B Wiestler, T Goldberg… - Physica medica, 2018 - Elsevier
Purpose Noticing the fast growing translation of artificial intelligence (AI) technologies to
medical image analysis this paper emphasizes the future role of the medical physicist in this …

[HTML][HTML] Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization

P Papadimitroulas, L Brocki, NC Chung, W Marchadour… - Physica Medica, 2021 - Elsevier
Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI)
field. Modern radiation oncology is based on the exploitation of advanced computational …

Deep learning with radiomics for disease diagnosis and treatment: challenges and potential

X Zhang, Y Zhang, G Zhang, X Qiu, W Tan, X Yin… - Frontiers in …, 2022 - frontiersin.org
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …

[HTML][HTML] The role of deep learning and radiomic feature extraction in cancer-specific predictive modelling: a review

A Vial, D Stirling, M Field, M Ros, C Ritz… - Translational Cancer …, 2018 - tcr.amegroups.org
This paper reviews objective methods for prognostic modelling of cancer tumours located
within radiology images, a process known as radiomics. Radiomics is a novel feature …

Radiomics and radiogenomics for precision radiotherapy

J Wu, KK Tha, L Xing, R Li - Journal of radiation research, 2018 - academic.oup.com
Imaging plays an important role in the diagnosis and staging of cancer, as well as in
radiation treatment planning and evaluation of therapeutic response. Recently, there has …

From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities

P Afshar, A Mohammadi, KN Plataniotis… - IEEE Signal …, 2019 - ieeexplore.ieee.org
Recent advancements in signal processing (SP) and machine learning, coupled with
electronic medical record keeping in hospitals and the availability of extensive sets of …