AIMC Topic: Reproducibility of Results

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Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

European journal of radiology Feb 7, 2025
PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small renal lesions (≤4 cm in diameter). This study aimed to integrate clinical data, radiomic features, a...
Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Kidney Neoplasms Carcinoma, Renal Cell Radiomics Reproducibility of Results Male Aged Middle Aged Aged, 80 and over Deep Learning Adult Humans Sensitivity and Specificity Retrospective Studies Tomography, X-Ray Computed Female
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An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs.

Nutrients Feb 7, 2025
: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This study aimed to evaluate the accuracy of ChatGPT-4 in estimatin...
Nutritive Value Humans Reproducibility of Results Diet Surveys Artificial Intelligence Nutrition Assessment Meals Generative Artificial Intelligence Photography Nutrients
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Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study.

Cardiovascular diabetology Feb 7, 2025
BACKGROUND: Cardiovascular complications are major concerns for Chinese patients with type 2 diabetes. Accurately predicting these risks remains challenging due to limitations in traditional risk models. We aimed to develop a dynamic prediction model...
Time Factors Diabetes Mellitus, Type 2 East Asian People Predictive Value of Tests Heart Disease Risk Factors Cardiovascular Diseases Female Middle Aged Machine Learning Reproducibility of Results Risk Assessment Decision Support Techniques Aged China Prognosis Male Humans
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Optimizing MR-based attenuation correction in hybrid PET/MR using deep learning: validation with a flatbed insert and consistent patient positioning.

European journal of nuclear medicine and molecular imaging Feb 6, 2025
PURPOSE: To address the challenges of verifying MR-based attenuation correction (MRAC) in PET/MR due to CT positional mismatches and alignment issues, this study utilized a flatbed insert and arms-down positioning during PET/CT scans to achieve preci...
Female Reproducibility of Results Aged Adult Humans Magnetic Resonance Imaging Multimodal Imaging Positron Emission Tomography Computed Tomography Fluorodeoxyglucose F18 Patient Positioning Male Middle Aged Deep Learning Image Processing, Computer-Assisted
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Quantification of tissue stiffness with magnetic resonance elastography and finite difference time domain (FDTD) simulation-based spatiotemporal neural network.

Magnetic resonance imaging Feb 4, 2025
Quantification of tissue stiffness with magnetic resonance elastography (MRE) is an inverse problem that is sensitive to noise. Conventional methods for the purpose include direct inversion (DI) and local frequency estimation (LFE). In this study, we...
Signal-To-Noise Ratio Phantoms, Imaging Elastic Modulus Elasticity Imaging Techniques Computer Simulation Reproducibility of Results Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Machine Learning-based World Health Organization Disability Assessment Schedule for persons with Parkinson's disease.

Parkinsonism & related disorders Feb 4, 2025
INTRODUCTION: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-known measure to assess disability in persons with Parkinson's disease (PD). The purpose of this study was to develop a short form of the WHODAS 2.0...
Humans Machine Learning Female Reproducibility of Results Aged Disability Evaluation Male World Health Organization Middle Aged Parkinson Disease
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Automated detection of early-stage osteonecrosis of the femoral head in adult using YOLOv10: Multi-institutional validation.

European journal of radiology Feb 4, 2025
OBJECTIVES: To develop a deep learning model based on the You Only Look Once version 10 (YOLOv10) for detecting early-stage ONFH in adult using radiographs.
Middle Aged Female Humans Reproducibility of Results Deep Learning Retrospective Studies Adult Magnetic Resonance Imaging Femur Head Necrosis Male Femur Head
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Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper.

BMC medical informatics and decision making Feb 4, 2025
Training machine learning models using data from severe COVID-19 patients admitted to a central hospital, where entire wards are specifically dedicated to COVID-19, may yield predictions that differ significantly from those generated using data colle...
Reproducibility of Results SARS-CoV-2 Information Dissemination Humans Artificial Intelligence Machine Learning COVID-19
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Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.

Journal of cardiovascular computed tomography Feb 4, 2025
BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, using features from CTCS images, we developed a novel machine learning model to predict obstructive coro...
Female Reproducibility of Results Risk Factors Aged Male Humans Machine Learning Decision Support Techniques Prognosis Vascular Calcification Computed Tomography Angiography Pericardium Epicardial Adipose Tissue Predictive Value of Tests Middle Aged Coronary Angiography Risk Assessment Coronary Artery Disease Severity of Illness Index Coronary Vessels Adipose Tissue
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The external validity of machine learning-based prediction scores from hematological parameters of COVID-19: A study using hospital records from Brazil, Italy, and Western Europe.

PloS one Feb 4, 2025
The unprecedented worldwide pandemic caused by COVID-19 has motivated several research groups to develop machine-learning based approaches that aim to automate the diagnosis or screening of COVID-19, in large-scale. The gold standard for COVID-19 det...
Adult Europe Humans Male Female Italy Machine Learning Middle Aged Reproducibility of Results Pandemics Brazil SARS-CoV-2 COVID-19 Aged
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