AIMC Topic: Retrospective Studies

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Accelerating prostate rs-EPI DWI with deep learning: Halving scan time, enhancing image quality, and validating in vivo.

Magnetic resonance imaging
OBJECTIVES: This study aims to evaluate the feasibility and effectiveness of deep learning-based super-resolution techniques to reduce scan time while preserving image quality in high-resolution prostate diffusion-weighted imaging (DWI) with readout-...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

The Journal of asthma : official journal of the Association for the Care of Asthma
PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged hospitalization in asthma patients.

Automatic detection of mandibular fractures on CT scan using deep learning.

Dento maxillo facial radiology
OBJECTIVES: This study explores the application of artificial intelligence (AI), specifically deep learning, in the detection and classification of mandibular fractures using CT scans.

Application of deep learning for detection of nasal bone fracture on X-ray nasal bone lateral view.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to assess the efficacy of deep learning applications for the detection of nasal bone fracture on X-ray nasal bone lateral view.

GPT4LFS (generative pretrained transformer 4 omni for lumbar foramina stenosis): enhancing lumbar foraminal stenosis image classification through large multimodal models.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Lumbar foraminal stenosis (LFS) is a common spinal condition that requires accurate assessment. Current magnetic resonance imaging (MRI) reporting processes are often inefficient, and while deep learning has potential for improvem...

Evaluation of error detection and treatment recommendations in nucleic acid test reports using ChatGPT models.

Clinical chemistry and laboratory medicine
OBJECTIVES: Accurate medical laboratory reports are essential for delivering high-quality healthcare. Recently, advanced artificial intelligence models, such as those in the ChatGPT series, have shown considerable promise in this domain. This study a...

Deep Learning-Based Fully Automated Aortic Valve Leaflets and Root Measurement From Computed Tomography Images - A Feasibility Study.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: The aim of this study was to retrain our existing deep learning-based fully automated aortic valve leaflets/root measurement algorithm, using computed tomography (CT) data for root dilatation (RD), and assess its clinical feasibility.

[Development of a machine learning-based diagnostic model for T-shaped uterus using transvaginal 3D ultrasound quantitative parameters].

Zhonghua yi xue za zhi
To develop a machine learning diagnostic model for T-shaped uterus based on quantitative parameters from 3D transvaginal ultrasound. A retrospective cross-sectional study was conducted, recruiting 304 patients who visited the hysteroscopy centre of...

Understanding Clinicians' Usage Patterns of the CONCERN Early Warning System: Insights from a Multi-Site Pragmatic Cluster Randomized Controlled Trial.

Studies in health technology and informatics
The CONCERN Early Warning System (EWS) uses artificial intelligence (AI) to analyze nursing documentation patterns, predicting hospitalized patients' risk of clinical deterioration. It generates real-time risk scores displayed on the electronic healt...