AIMC Topic: Reproducibility of Results

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Deep learning algorithm enables automated Cobb angle measurements with high accuracy.

Skeletal radiology Dec 17, 2024
OBJECTIVE: To determine the accuracy of automatic Cobb angle measurements by deep learning (DL) on full spine radiographs.
Child, Preschool Child Radiographic Image Interpretation, Computer-Assisted Scoliosis Adult Male Middle Aged Deep Learning Adolescent Humans Algorithms Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Young Adult
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Incorporating Radiologist Knowledge Into MRI Quality Metrics for Machine Learning Using Rank-Based Ratings.

Journal of magnetic resonance imaging : JMRI Dec 17, 2024
BACKGROUND: Deep learning (DL) often requires an image quality metric; however, widely used metrics are not designed for medical images.
Humans Neural Networks, Computer Machine Learning Algorithms Databases, Factual Image Processing, Computer-Assisted Magnetic Resonance Imaging Radiologists Image Interpretation, Computer-Assisted Brain Retrospective Studies Reproducibility of Results Deep Learning
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Assessing the performance of chat generative pretrained transformer (ChatGPT) in answering chronic kidney disease-related questions.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy Dec 16, 2024
BACKGROUND: Chatbots produced by artificial intelligence are frequently used in health information today. We aimed to investigate the reliability and reproducibility of the answers given by Chat Generative Pretrained Transformer (ChatGPT), one of the...
Humans Surveys and Questionnaires Generative Artificial Intelligence Renal Insufficiency, Chronic Social Media Internet Artificial Intelligence Female Reproducibility of Results Male Middle Aged
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Artificial intelligence-assisted fitting method using corneal topography outcomes enhances success rate in orthokeratology lens fitting.

Contact lens & anterior eye : the journal of the British Contact Lens Association Dec 16, 2024
PURPOSE: Based on ideal outcomes of corneal topography following orthokeratology (OK), an innovative machine learning algorithm for corneal refractive therapy (CRT) was developed to investigate the precision of artificial intelligence (AI)-assisted O...
Female Reproducibility of Results Young Adult Adult Male Humans Artificial Intelligence Algorithms Retrospective Studies Prosthesis Fitting Orthokeratologic Procedures Child Treatment Outcome Visual Acuity Middle Aged Corneal Topography Refraction, Ocular Contact Lenses Myopia Adolescent
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Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT.

Artificial intelligence in medicine Dec 16, 2024
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predi...
Lung Neoplasms Early Detection of Cancer Radiation Dosage Proof of Concept Study Uncertainty Reproducibility of Results Aged Male Middle Aged Risk Assessment Humans Artificial Intelligence Tomography, X-Ray Computed Female
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Artificial intelligence-derived coronary artery calcium scoring saves time and achieves close to radiologist-level accuracy accuracy on routine ECG-gated CT.

The international journal of cardiovascular imaging Dec 16, 2024
Artificial Intelligence (AI) has been proposed to improve workflow for coronary artery calcium scoring (CACS), but simultaneous demonstration of improved efficiency, accuracy, and clinical stability have not been demonstrated. 148 sequential patients...
Female Reproducibility of Results Aged Male Middle Aged Humans Artificial Intelligence Retrospective Studies Coronary Vessels Multidetector Computed Tomography Vascular Calcification Computed Tomography Angiography Cardiac-Gated Imaging Techniques Severity of Illness Index Time Factors Electrocardiography Predictive Value of Tests Coronary Angiography Radiologists Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Workflow Observer Variation
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Blood Pressure Estimation Using Explainable Deep-Learning Models Based on Photoplethysmography.

Anesthesia and analgesia Dec 16, 2024
BACKGROUND: Due to their invasiveness, arterial lines are not typically used in routine monitoring, despite their superior responsiveness in hemodynamic monitoring and detecting intraoperative hypotension. To address this issue, noninvasive, continuo...
Arterial Pressure Humans Deep Learning Monitoring, Intraoperative Photoplethysmography Blood Pressure Determination Predictive Value of Tests Female Reproducibility of Results Aged Male Middle Aged
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A quality assessment tool for focused abdominal sonography for trauma examinations using artificial intelligence.

The journal of trauma and acute care surgery Dec 14, 2024
BACKGROUND: Current tools to review focused abdominal sonography for trauma (FAST) images for quality have poorly defined grading criteria or are developed to grade the skills of the sonographer and not the examination. The purpose of this study is t...
Reproducibility of Results Clinical Competence Ultrasonography Quality Assurance, Health Care Abdominal Injuries Humans Artificial Intelligence Focused Assessment with Sonography for Trauma
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Conditional generative diffusion deep learning for accelerated diffusion tensor and kurtosis imaging.

Magnetic resonance imaging Dec 13, 2024
PURPOSE: The purpose of this study was to develop DiffDL, a generative diffusion probabilistic model designed to produce high-quality diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics from a reduced set of diffusion-weighted...
Adult Male Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Connectome Diffusion Tensor Imaging Anisotropy Diffusion Magnetic Resonance Imaging Humans Algorithms Brain Female Reproducibility of Results
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Individual risk assessment for rupture of abdominal aortic aneurysm using artificial intelligence.

Journal of vascular surgery Dec 13, 2024
OBJECTIVE: This study aimed to develop a prediction tool to identify abdominal aortic aneurysms (AAAs) at increased risk of rupture incorporating demographic, clinical, imaging, and medication data using artificial intelligence (AI).
Aortography Aortic Rupture Aged, 80 and over Male Middle Aged Risk Assessment Case-Control Studies Decision Trees Denmark Predictive Value of Tests Aortic Aneurysm, Abdominal Computed Tomography Angiography Retrospective Studies Female Reproducibility of Results Risk Factors Aged Humans Artificial Intelligence Decision Support Techniques Prognosis
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