Urology

Cardiac autonomic dysfunction in patients with multiple system atrophy and spinocerebellar ataxia: A comparative study and distinctive machine learning model.

BACKGROUND: Differentiating multiple system atrophy-cerebellar subtype (MSA-C) from spinocerebellar ataxia (SCA) is often difficult due to overlapping cerebellar and autonomic manifestations. Heart rate variability (HRV) provides a noninvasive measure of cardiac autonomic function and may reveal distinct disease-specific patterns. METHODS: In this cross-sectional study, 22 patients with MSA-C, 22 ...

Diagnostic text-guided representation learning in hierarchical classification for pathological whole slide image.

With the development of digital imaging in medical microscopy, artificial intelligent-based analysis of pathological whole slide images (WSIs) provides a powerful tool for cancer diagnosis. Limited by the expensive cost of pixel-level annotation, current research primarily focuses on representation learning with slide-level labels, showing success in various downstream tasks. However, given the di...

Artificial Intelligence in Prostate MRI: Addressing Current Limitations Through Emerging Technologies.

Prostate MRI has transformed lesion detection and risk stratification in prostate cancer, but its impact is constrained by the high cost of the exam, ...

The global epidemiology of acute kidney injury: challenges and opportunities.

Acute kidney injury (AKI) is a devastating complication of acute illness that affects adults and children across multiple settings worldwide and is as...

Emerging biomarkers in prostate cancer diagnosis and treatment: Insights into genetic, RNA and metabolic markers (Review).

Prostate cancer remains one of the most prevalent malignancies and a major cause of cancer‑related mortality among men worldwide. Despite widespread u...

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster in patients with lung cancer following chemotherap...

Artificial intelligence and multi-omics integration in liquid biopsy for genitourinary cancers: a systematic scoping review.

BACKGROUND: Liquid biopsy, combined with multi-omics profiling and artificial intelligence (AI), offers a minimally invasive strategy for cancer detec...

Trajectories in renal perfusion pressure during hemodynamically guided therapy are associated with worsening renal function and patient outcomes.

BACKGROUND: Worsening renal function (WRF) during acute decompensated heart failure (ADHF) therapy portends worse outcomes. We hypothesized that renal...

Machine Learning for Classification in Lung Cancer Using Routine Clinical and Laboratory Data.

BACKGROUND: Accurate pathological classification of lung cancer is essential for informing treatment strategies. However, invasive biopsy procedures a...

Artificial intelligence diagnostics for bladder tumor identification and grade prediction depend on narrow band imaging cystoscopy.

The effective treatment of bladder cancer depends on early evaluation through cystoscopy. Given the clinical importance of distinguishing the tumor gr...

From macroscopic clearance to molecular eradication: paradigm shift and future perspectives in the detecting of residual lesions after transurethral resection of bladder tumors.

INTRODUCTION: Residual lesions after transurethral resection of bladder tumor (TURBT) are a major contributor to recurrence in bladder cancer. Advance...

Reply to comment on impact of deep learning on CT-based organ-at-risk delineation for flank irradiation in paediatric renal tumours: A SIOP-RTSG radiotherapy committee.

We appreciate the commentary from Saad et al., which offers an opportunity to clarify key methodological and clinical aspects of our study assessing t...

The role of artificial intelligence in advancing urologic care: From diagnostics to therapeutics.

Artificial intelligence (AI) is gradually altering urology by improving diagnostic precision, prognostic evaluation, and therapy decisions in a broad ...

Digital health integration in chronic kidney disease.

Chronic kidney disease (CKD) is a growing global health burden characterized by progressive renal dysfunction, high comorbidity rates, and substantial...

Ethical challenges in kidney transplantation.

PURPOSE OF REVIEW: This review provides a comprehensive examination of the current inequities and ethical challenges in kidney transplantation and hig...

Interpretable machine learning for urothelial cells classification and risk scoring in urine cytology.

Urine cytology is widely used for detecting urothelial carcinoma (UC), though its performance is constrained by limited sensitivity and substantial in...

Feasibility of transperineal prostate biopsy guided by fusion of [18F]F-PSMA-1007 PET/MRI with real-time transrectal ultrasound. Prostate cancer classification using imaging biomarkers and radiomics in PIRADS 3 lesions.

OBJECTIVE: To assess the diagnostic feasibility of transperineal biopsy guided by fusion of PET/MRI with [18F]F-PSMA-1007 and real-time transrectal ul...

Automated Recognition and Measurement for Levator Hiatus in 3D Ultrasound: A Clinical Study in Postpartum Women.

OBJECTIVES: To evaluate the performance of a CNN-based (convolutional neural networks-based) AI software for automatic recognition and measurement of ...

Context-aware heterogeneous graph neural network for multi-level description and invasiveness prediction in renal cell carcinoma.

The invasiveness prediction in renal cell carcinoma (RCC) is of significant importance for the decision of clinical surgical plans and the patients' p...

Hereditary syndromes and RCC: what radiologists need to know.

Hereditary renal cell carcinoma (RCC) accounts for approximately 5-8% of all renal cancers. This review provides a comprehensive overview of the seven...