Biodegradable implantable sensors: materials design, fabrication, and applications

N Ashammakhi, AL Hernandez… - Advanced Functional …, 2021 - Wiley Online Library
The ability to monitor diseases, therapies, and their effects on the body is a critical
component of modern care and personalized medicine. Real time monitoring can be …

Automated classification of significant prostate cancer on MRI: a systematic review on the performance of machine learning applications

JM Castillo T, M Arif, WJ Niessen, IG Schoots… - Cancers, 2020 - mdpi.com
Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep
learning approaches has gained much interest, due to the potential application in assisting …

Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to …

L Fournier, L Costaridou, L Bidaut, N Michoux… - European …, 2021 - Springer
Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue
characteristics and follow a well-understood path of technical, biological and clinical …

Pre-treatment T2-WI based radiomics features for prediction of locally advanced rectal cancer non-response to neoadjuvant chemoradiotherapy: a preliminary study

B Petresc, A Lebovici, C Caraiani, DS Feier, F Graur… - Cancers, 2020 - mdpi.com
Locally advanced rectal cancer (LARC) response to neoadjuvant chemoradiotherapy
(nCRT) is very heterogeneous and up to 30% of patients are considered non-responders …

The diagnosis of tuberculous meningitis: advancements in new technologies and machine learning algorithms

Y Shi, C Zhang, S Pan, Y Chen, X Miao, G He… - Frontiers in …, 2023 - frontiersin.org
Tuberculous meningitis (TBM) poses a diagnostic challenge, particularly impacting
vulnerable populations such as infants and those with untreated HIV. Given the diagnostic …

A machine learning-based predictive model for predicting lymph node metastasis in patients with ewing's sarcoma

W Li, Q Zhou, W Liu, C Xu, ZR Tang, S Dong… - Frontiers in …, 2022 - frontiersin.org
Objective In order to provide reference for clinicians and bring convenience to clinical work,
we seeked to develop and validate a risk prediction model for lymph node metastasis (LNM) …

The constantly evolving role of medical image processing in oncology: from traditional medical image processing to imaging biomarkers and radiomics

K Marias - Journal of imaging, 2021 - mdpi.com
The role of medical image computing in oncology is growing stronger, not least due to the
unprecedented advancement of computational AI techniques, providing a technological …

Preoperative predicting the WHO/ISUP nuclear grade of clear cell renal cell carcinoma by computed tomography-based radiomics features

CG Moldovanu, B Boca, A Lebovici… - Journal of personalized …, 2020 - mdpi.com
Nuclear grade is important for treatment selection and prognosis in patients with clear cell
renal cell carcinoma (ccRCC). This study aimed to determine the ability of preoperative four …

Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically driven quantitative biomarkers

L Fournier, L Costaridou, L Bidaut, N Michoux… - … Radiology: journal of …, 2021 - repub.eur.nl
Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue
characteristics and follow a well-understood path of technical, biological and clinical …

Prediction of TACE treatment response in a preoperative MRI via analysis of integrating deep learning and radiomics features

Y Tian, TE Komolafe, T Chen, B Zhou… - Journal of Medical and …, 2022 - Springer
Purpose To evaluate the efficiency of an integrated model on MRI scans of hepatocellular
carcinoma (HCC) patients for preoperative prediction of transcatheter arterial …