Urology

MRI-based prostate cancer classification using 3D efficient capsule network.

BACKGROUND: Prostate cancer (PCa) is the most common cancer in men and the second leading cause of male cancer-related death. Gleason score (GS) is the primary driver of PCa risk-stratification and medical decision-making, but can only be assessed at present via biopsy under anesthesia. Magnetic resonance imaging (MRI) is a promising non-invasive method to further characterize PCa, providing addit...

Effect of Febuxostat versus Allopurinol on the Glomerular Filtration Rate and Hyperuricemia in Patients with Chronic Kidney Disease.

Hyperuricemia is a risk factor for the progression of chronic kidney disease (CKD). We compared febuxostat versus allopurinol in the progression of CKD and hyperuricemia in 101 patients with Stage 3-4 CKD treated with febuxostat or allopurinol for at least 6 months for hyperuricemia (>7 mg/dL) between January 2012 and December 2016. Baseline characteristics, serum uric acid (SUA), serum creatinine...

Acute Kidney Injury in Acute Myocardial Infarction and Its Outcome at 3 and 6 Months.

Epidemiological data on the prevalence of acute kidney injury (AKI) in acute coronary syndrome are sparse, with most studies having been conducted ret...

Study of Serum Fibroblast Growth Factor 23 as a Predictor of Endothelial Dysfunction among Egyptian Patients with Diabetic Kidney Disease.

Endothelial dysfunction in patients with diabetic nephropathy is caused by nontraditional factors in addition to common risk factors (e.g., hypertensi...

Prediction of spontaneous distal ureteral stone passage using artificial intelligence.

PURPOSE: Identifying factors predicting the spontaneous passage of distal ureteral stones and evaluating the effectiveness of artificial intelligence ...

ASD-Net: a novel U-Net based asymmetric spatial-channel convolution network for precise kidney and kidney tumor image segmentation.

Early intervention in tumors can greatly improve human survival rates. With the development of deep learning technology, automatic image segmentation ...

Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance.

This study aimed to assess the performance of a deep learning algorithm in helping radiologist achieve improved efficiency and accuracy in chest radio...

Robotic Radical Cystectomy for Bladder Cancer: The Way Forward.

The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.

We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled Na...

AIEgen-deep: Deep learning of single AIEgen-imaging pattern for cancer cell discrimination and preclinical diagnosis.

This study introduces AIEgen-Deep, an innovative classification program combining AIEgen fluorescent dyes, deep learning algorithms, and the Segment A...

Custom-Trained Deep Learning-Based Auto-Segmentation for Male Pelvic Iterative CBCT on C-Arm Linear Accelerators.

PURPOSE: The purpose of this investigation was to evaluate the clinical applicability of a commercial artificial intelligence-driven deep learning aut...

Donor hepatitis C status is not associated with an increased risk of acute rejection in kidney transplantation.

INTRODUCTION: In renal transplantation, donor hepatitis C virus (HCV) status is crucial to consider when selecting a recipient given the high likeliho...

Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease.

BACKGROUND: Non-invasive renal fibrosis assessment is critical for tailoring personalized decision-making and managing follow-up in patients with chro...

Interactive content-based image retrieval with deep learning for CT abdominal organ recognition.

Recognizing the most relevant seven organs in an abdominal computed tomography (CT) slice requires sophisticated knowledge. This study proposed automa...

Deep learning algorithm-based multimodal MRI radiomics and pathomics data improve prediction of bone metastases in primary prostate cancer.

PURPOSE: Bone metastasis is a significant contributor to morbidity and mortality in advanced prostate cancer, and early diagnosis is challenging due t...

External Validation of a Digital Pathology-based Multimodal Artificial Intelligence Architecture in the NRG/RTOG 9902 Phase 3 Trial.

BACKGROUND: Accurate risk stratification is critical to guide management decisions in localized prostate cancer (PCa). Previously, we had developed an...

Deep Learning Based on ResNet-18 for Classification of Prostate Imaging-Reporting and Data System Category 3 Lesions.

RATIONALE AND OBJECTIVES: To explore the classification and prediction efficacy of the deep learning model for benign prostate lesions, non-clinically...

Radiologists' perspectives on the workflow integration of an artificial intelligence-based computer-aided detection system: A qualitative study.

In healthcare, artificial intelligence (AI) is expected to improve work processes, yet most research focuses on the technical features of AI rather th...

Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit.

BACKGROUND AND OBJECTIVE: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes...

A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.

Urinary tract infection (UTI) is a common disorder. Its diagnosis can be made by microscopic examination of voided urine for markers of infection. Thi...