AIMC Topic: Reproducibility of Results

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Deep learning algorithm for automatically measuring Cobb angle in patients with idiopathic scoliosis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Feb 17, 2024
PURPOSE: The Cobb angle is a standard measurement to qualify and track the progression of scoliosis. However, the Cobb angle has high inter- and intra-observer variability. Consequently, its measurement varies with vertebrae and may even differ when ...
Scoliosis Child Radiography Spine Deep Learning Adolescent Humans Female Reproducibility of Results Male
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OMERACT validation of a deep learning algorithm for automated absolute quantification of knee joint effusion versus manual semi-quantitative assessment.

Seminars in arthritis and rheumatism Feb 17, 2024
OBJECTIVE: To begin evaluating deep learning (DL)-automated quantification of knee joint effusion-synovitis via the OMERACT filter.
Knee Joint Osteoarthritis, Knee Middle Aged Deep Learning Magnetic Resonance Imaging Reproducibility of Results Aged Humans Male Algorithms Female
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Classification of self-limited epilepsy with centrotemporal spikes by classical machine learning and deep learning based on electroencephalogram data.

Brain research Feb 17, 2024
Electroencephalogram (EEG) has been widely utilized as a valuable assessment tool for diagnosing epilepsy in hospital settings. However, clinical diagnosis of patients with self-limited epilepsy with centrotemporal spikes (SeLECTS) is challenging due...
Machine Learning Reproducibility of Results Deep Learning Child, Preschool Humans Epilepsy Child Electroencephalography
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Application of the performance of machine learning techniques as support in the prediction of school dropout.

Scientific reports Feb 17, 2024
This article presents a study, intending to design a model with 90% reliability, which helps in the prediction of school dropouts in higher and secondary education institutions, implementing machine learning techniques. The collection of information ...
Bayes Theorem Machine Learning Student Dropouts Reproducibility of Results Support Vector Machine Humans Neural Networks, Computer
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Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3.

Journal of magnetic resonance imaging : JMRI Feb 16, 2024
BACKGROUND: For patients with PI-RADS v2.1 ≥ 3, prostate biopsy is strongly recommended. Due to the unsatisfactory positive rate of biopsy, improvements in clinically significant prostate cancer (csPCa) risk assessments are required.
Reproducibility of Results Aged Male Humans Machine Learning Retrospective Studies Magnetic Resonance Imaging Prostatic Neoplasms Prostate-Specific Antigen Middle Aged Risk Assessment ROC Curve Diffusion Magnetic Resonance Imaging Echo-Planar Imaging Prostate Biopsy Image Interpretation, Computer-Assisted
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Automation and Computerization of (Bio)sensing Systems.

ACS sensors Feb 16, 2024
Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection an...
Artificial Intelligence Reproducibility of Results Humans Microfluidics Robotics Automation
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Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation.

Journal of veterinary internal medicine Feb 16, 2024
BACKGROUND: Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiographic measurements in dogs.
Dogs Heart Ventricles Diastole Reproducibility of Results Animals Echocardiography Artificial Intelligence
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Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study.

Nutrition, metabolism, and cardiovascular diseases : NMCD Feb 15, 2024
BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate pot...
Predictive Value of Tests Non-alcoholic Fatty Liver Disease Risk Assessment Decision Support Techniques Diagnosis, Computer-Assisted Biomarkers Beijing Humans Adult Female Machine Learning Longitudinal Studies Reproducibility of Results Prognosis Risk Factors Male Middle Aged
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Prediction of Aureococcus anophageffens using machine learning and deep learning.

Marine pollution bulletin Feb 15, 2024
The recurrent brown tide phenomenon, attributed to Aureococcus anophagefferens (A. anophagefferens), constitutes a significant threat to the Qinhuangdao sea area in China, leading to pronounced ecological degradation and substantial economic losses. ...
Machine Learning Reproducibility of Results Deep Learning Nitrogen Stramenopiles
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Exploring the role of large language models in radiation emergency response.

Journal of radiological protection : official journal of the Society for Radiological Protection Feb 15, 2024
In recent times, the field of artificial intelligence (AI) has been transformed by the introduction of large language models (LLMs). These models, popularized by OpenAI's GPT-3, have demonstrated the emergent capabilities of AI in comprehending and p...
Reproducibility of Results Humans Emergencies Artificial Intelligence Industry Language
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