Radiogenomics in renal cancer management—current evidence and future prospects

M Ferro, G Musi, M Marchioni, M Maggi… - International journal of …, 2023 - mdpi.com
Renal cancer management is challenging from diagnosis to treatment and follow-up. In
cases of small renal masses and cystic lesions the differential diagnosis of benign or …

Novel imaging methods for renal mass characterization: a collaborative review

E Roussel, U Capitanio, A Kutikov, E Oosterwijk… - European urology, 2022 - Elsevier
Context The incidental detection of localized renal masses has been rising steadily, but a
significant proportion of these tumors are benign or indolent and, in most cases, do not …

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

M Ferro, F Crocetto, B Barone… - Therapeutic …, 2023 - journals.sagepub.com
Radiomics and artificial intelligence (AI) may increase the differentiation of benign from
malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma …

Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review

M Lubbad, D Karaboga, A Basturk, B Akay… - Neural Computing and …, 2024 - Springer
Deep learning integration in cancer diagnosis enhances accuracy and diagnosis speed
which helps clinical decision-making and improves health outcomes. Despite all these …

Artificial intelligence in urooncology: what we have and what we expect

A Froń, A Semianiuk, U Lazuk, K Ptaszkowski… - Cancers, 2023 - mdpi.com
Simple Summary Our study provides an overview of the current state of artificial intelligence
applications in urooncology and explores potential future advancements in this field. With …

The cancer multidisciplinary team meeting: in need of change? History, challenges and future perspectives

DA Winters, T Soukup, N Sevdalis, JSA Green… - BJU …, 2021 - Wiley Online Library
Two decades since their inception, multidisciplinary teams (MDTs) are widely regarded as
the 'gold standard'of cancer care delivery. Benefits of MDT working include improved patient …

Development and validation of a deep-learning model to assist with renal cell carcinoma histopathologic interpretation

M Fenstermaker, SA Tomlins, K Singh, J Wiens… - Urology, 2020 - Elsevier
OBJECTIVE To develop and test the ability of a convolutional neural network (CNN) to
accurately identify the presence of renal cell carcinoma (RCC) on histopathology …

Radiomics applications in renal tumor assessment: a comprehensive review of the literature

R Suarez-Ibarrola, M Basulto-Martinez, A Heinze… - Cancers, 2020 - mdpi.com
Radiomics texture analysis offers objective image information that could otherwise not be
obtained by radiologists′ subjective radiological interpretation. We investigated radiomics …

Applications of neural networks in urology: a systematic review

E Checcucci, S De Cillis, S Granato… - Current Opinion in …, 2020 - journals.lww.com
In urological medicine, the application of novel artificial intelligence technologies,
particularly ANNs, have been considered to be a promising step in improving physicians' …

Advances in imaging-based biomarkers in renal cell carcinoma: a critical analysis of the current literature

L Posada Calderon, L Eismann, SW Reese, E Reznik… - Cancers, 2023 - mdpi.com
Simple Summary Current imaging techniques do not reliably distinguish renal cell
carcinoma from other renal diseases. This review summarizes recent advances in other …