Radiomics and radiogenomics in gliomas: a contemporary update

G Singh, S Manjila, N Sakla, A True, AH Wardeh… - British journal of …, 2021 - nature.com
The natural history and treatment landscape of primary brain tumours are complicated by the
varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low …

Biobanking in health care: evolution and future directions

L Coppola, A Cianflone, AM Grimaldi… - Journal of translational …, 2019 - Springer
Background The aim of the present review is to discuss how the promising field of
biobanking can support health care research strategies. As the concept has evolved over …

A machine learning approach to diagnosing lung and colon cancer using a deep learning-based classification framework

M Masud, N Sikder, AA Nahid, AK Bairagi, MA AlZain - Sensors, 2021 - mdpi.com
The field of Medicine and Healthcare has attained revolutionary advancements in the last
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …

Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas

N Beig, M Khorrami, M Alilou, P Prasanna, N Braman… - Radiology, 2019 - pubs.rsna.org
Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish
non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials …

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 …

Harnessing non-destructive 3D pathology

JTC Liu, AK Glaser, K Bera, LD True… - Nature biomedical …, 2021 - nature.com
High-throughput methods for slide-free three-dimensional (3D) pathological analyses of
whole biopsies and surgical specimens offer the promise of modernizing traditional …

[HTML][HTML] Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images

I Shiri, M Amini, M Nazari, G Hajianfar, AH Avval… - Computers in biology …, 2022 - Elsevier
Objective To investigate the impact of harmonization on the performance of CT, PET, and
fused PET/CT radiomic features toward the prediction of mutations status, for epidermal …

Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine

MK Santos, JR Ferreira, DT Wada, APM Tenório… - Radiologia …, 2019 - SciELO Brasil
The discipline of radiology and diagnostic imaging has evolved greatly in recent years. We
have observed an exponential increase in the number of exams performed …

Lung cancer histology classification from CT images based on radiomics and deep learning models

P Marentakis, P Karaiskos, V Kouloulias… - Medical & biological …, 2021 - Springer
Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are frequent reported cases of
non-small cell lung cancer (NSCLC), responsible for a large fraction of cancer deaths …

The state of the art for artificial intelligence in lung digital pathology

VS Viswanathan, P Toro, G Corredor… - The Journal of …, 2022 - Wiley Online Library
Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of
digital pathology (DP) and an increase in computational power have led to the development …