AIMC Topic: Retrospective Studies

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Deep learning-based whole-body characterization of prostate cancer lesions on [Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence.

European journal of nuclear medicine and molecular imaging
PURPOSE: The automatic segmentation and detection of prostate cancer (PC) lesions throughout the body are extremely challenging due to the lesions' complexity and variability in appearance, shape, and location. In this study, we investigated the perf...

Effectiveness of strategies to suppress antibodies to infliximab in pediatric inflammatory bowel disease.

Journal of pediatric gastroenterology and nutrition
OBJECTIVES: Antibodies to infliximab (ATIs) are associated with loss of response in children with inflammatory bowel disease (IBD). We aimed to describe the effectiveness of strategies for treatment modification following ATI development in pediatric...

Meningioma consistency assessment based on the fusion of deep learning features and radiomics features.

European journal of radiology
PURPOSE: This study aims to combine deep learning features with radiomics features for the computer-assisted preoperative assessment of meningioma consistency.

[Adrenal insufficiency as part of X-linked adrenoleukodystrophy].

Problemy endokrinologii
BACKGROUND:  X-linked adrenoleukodystrophy (X-ALD) is a severe neurodegenerative metabolic disease with a frequency 1:17,000 in newborn boys. Being a major part of X-ALD with an incidence of 70-80% of patients, adrenal insufficiency (AI) is a life-th...

Establishment of Biliary Atresia Prognostic Classification System via Survival-Based Forward Clustering - A New Biliary Atresia Classification.

Indian journal of pediatrics
OBJECTIVES: To develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide instructions for choosing treatment schemes.

Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study.

Biomedical engineering online
BACKGROUND: This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans.

Deep Learning-based Diagnosis and Localization of Pneumothorax on Portable Supine Chest X-ray in Intensive and Emergency Medicine: A Retrospective Study.

Journal of medical systems
PURPOSE: To develop two deep learning-based systems for diagnosing and localizing pneumothorax on portable supine chest X-rays (SCXRs).

A novel loss function to reproduce texture features for deep learning-based MRI-to-CT synthesis.

Medical physics
BACKGROUND: Studies on computed tomography (CT) synthesis based on magnetic resonance imaging (MRI) have mainly focused on pixel-wise consistency, but the texture features of regions of interest (ROIs) have not received appropriate attention.

Intraoral Microscopic Versus Robot-Assisted Sialolithotomy and Sialendoscopy for Submandibular Stones.

The Laryngoscope
OBJECTIVE: Sialendoscopy has remained the standard of treatment for sialolithiasis; however, large stones impacted in the submandibular gland hilum often require an intra-oral combined approach.