PURPOSE: To assess the predictive capability of hematological inflammatory markers for urethral stricture recurrence after primary urethroplasty and to compare traditional statistical methods with a machine-learning-based artificial intelligence algo...
Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models...
Investigative ophthalmology & visual science
May 1, 2024
PURPOSE: The purpose of this study was to investigate the incidence of foveal involvement in geographic atrophy (GA) secondary to age-related macular degeneration (AMD), using machine learning to assess the importance of risk factors.
Investigative ophthalmology & visual science
May 1, 2024
PURPOSE: Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and complicated by compressive optic neuropathy (CON). This study aims to utilize a deep-learning (DL)-based automated segmentation model to segment orbital muscl...
BACKGROUND/AIM: While post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) benefits patients with teratoma or viable germ cell tumors (GCT), it becomes overtreatment if necrosis is detected in PC-RPLND specimens. Serum microRNA-371a-3p ...
BACKGROUND: Capsule endoscopy reading is time consuming, and readers are required to maintain attention so as not to miss significant findings. Deep convolutional neural networks can recognise relevant findings, possibly exceeding human performances ...
BACKGROUND: Acute leukaemias are life-threatening haematological cancers characterised by the infiltration of transformed immature haematopoietic cells in the blood and bone marrow. Prompt and accurate diagnosis of the three main acute leukaemia subt...
BACKGROUND: In the context of immune-mediated inflammatory diseases (IMIDs), COVID-19 outcomes are incompletely understood and vary considerably depending on the patient population studied. We aimed to analyse severe COVID-19 outcomes and to investig...
Purpose To evaluate the ability of a semiautonomous artificial intelligence (AI) model to identify screening mammograms not suspicious for breast cancer and reduce the number of false-positive examinations. Materials and Methods The deep learning alg...
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