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 …
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
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 …
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 …
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 …
(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 …
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
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) …
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 …
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 …
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 …
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 …
carcinoma (HCC) patients for preoperative prediction of transcatheter arterial …