AIMC Topic: Reproducibility of Results

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The Low Rate of Adherence to Checklist for Artificial Intelligence in Medical Imaging Criteria Among Published Prostate MRI Artificial Intelligence Algorithms.

Journal of the American College of Radiology : JACR
OBJECTIVE: To determine the rigor, generalizability, and reproducibility of published classification and detection artificial intelligence (AI) models for prostate cancer (PCa) on MRI using the Checklist for Artificial Intelligence in Medical Imaging...

Machine Learning-Based Prediction Models for Delirium: A Systematic Review and Meta-Analysis.

Journal of the American Medical Directors Association
OBJECTIVE: To critically appraise and quantify the performance studies by employing machine learning (ML) to predict delirium.

: Intelligent Wireless System for Cost-Effective Rapid Condition Assessment of Bridges under Impacts.

Sensors (Basel, Switzerland)
Bridge strikes by over-height vehicles or ships are critical sudden events. Due to their unpredictable nature, many events go unnoticed or unreported, but they can induce structural failures or hidden damage that accelerates the bridge's long-term de...

Deep learning-based tool affects reproducibility of pes planus radiographic assessment.

Scientific reports
Angle measurement methods for measuring pes planus may lose consistency by errors between observers. If the feature points for angle measurement can be provided in advance with the algorithm developed through the deep learning method, it is thought t...

Evaluation and comparison of smartphone application tracing, web based artificial intelligence tracing and conventional hand tracing methods.

Journal of stomatology, oral and maxillofacial surgery
AIM: The aim of this study was to compare and evaluate the reliability of three different cephalometric assessment methods: Smartphone Application Tracing Method CephNinja (SATM), Web Based Artificial Intelligence (AI) Driven Tracing Method WebCeph (...

Optimisation of Deep Learning Small-Object Detectors with Novel Explainable Verification.

Sensors (Basel, Switzerland)
In this paper, we present a novel methodology based on machine learning for identifying the most appropriate from a set of available state-of-the-art object detectors for a given application. Our particular interest is to develop a road map for ident...

Patient safety classifications, taxonomies and ontologies: A systematic review on development and evaluation methodologies.

Journal of biomedical informatics
INTRODUCTION: Patient safety classifications/ontologies enable patient safety information systems to receive and analyze patient safety data to improve patient safety. Patient safety classifications/ontologies have been developed and evaluated using ...

End-to-end deep learning framework for printed circuit board manufacturing defect classification.

Scientific reports
We report a complete deep-learning framework using a single-step object detection model in order to quickly and accurately detect and classify the types of manufacturing defects present on Printed Circuit Board (PCBs). We describe the complete model ...

Artificial Intelligence and Cardiovascular Magnetic Resonance Imaging in Myocardial Infarction Patients.

Current problems in cardiology
Cardiovascular magnetic resonance (CMR) is an important cardiac imaging tool for assessing the prognostic extent of myocardial injury after myocardial infarction (MI). Within the context of clinical trials, CMR is also useful for assessing the effica...

Deep Learning Applications for Acute Stroke Management.

Annals of neurology
Brain imaging is essential to the clinical care of patients with stroke, a leading cause of disability and death worldwide. Whereas advanced neuroimaging techniques offer opportunities for aiding acute stroke management, several factors, including ti...