AIMC Topic: Carcinoma, Transitional Cell

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Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Decisions on the best available treatment in clinical oncology are based on expert opinions in multidisciplinary cancer conferences (MCC). Artificial intelligence (AI) could increase evidence-based treatment by generating additional treat...

Noninvasive identification of HER2 status by integrating multiparametric MRI-based radiomics model with the vesical imaging-reporting and data system (VI-RADS) score in bladder urothelial carcinoma.

Abdominal radiology (New York)
PURPOSE: HER2 expression is crucial for the application of HER2-targeted antibody-drug conjugates. This study aims to construct a predictive model by integrating multiparametric magnetic resonance imaging (mpMRI) based multimodal radiomics and the Ve...

Artificial intelligence algorithms enhance urine cytology reporting confidence in postoperative follow-up for upper urinary tract urothelial carcinoma.

International urology and nephrology
PURPOSE: In Taiwan, the incidence of urothelial carcinoma of the upper urinary tract (UTUC) is high and intravesical recurrence is approximately 22%-47%. Thus, postoperative cystoscopy and urine cytology follow-up, which require experienced cytologis...

Evaluating artificial intelligence-enhanced digital urine cytology for bladder cancer diagnosis.

Cancer cytopathology
BACKGROUND: This study evaluated the diagnostic effectiveness of the AIxURO platform, an artificial intelligence-based tool, to support urine cytology for bladder cancer management, which typically requires experienced cytopathologists and substantia...

Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma.

BMC cancer
BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated wit...

Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma: a step towards virtual biopsy.

International journal of surgery (London, England)
OBJECTIVES: Upper tract urothelial carcinoma (UTUC) is a rare, aggressive lesion, with early detection a key to its management. This study aimed to utilise computed tomographic urogram data to develop machine learning models for predicting tumour gra...

[What contribution can make artificial intelligence to urinary cytology?].

Annales de pathologie
Urinary cytology using the Paris system is still the method of choice for screening high-grade urothelial carcinomas. However, the use of the objective criteria described in this terminology shows a lack of inter- and intra-observer reproducibility. ...

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments.

Virchows Archiv : an international journal of pathology
Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial i...

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

Histopathology
AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between path...