AIMC Topic: Reproducibility of Results

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Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis.

ACS sensors
A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identificati...

Deep Learning-Based Prognostics and Health Management Model for Pilot-Operated Cryogenic Safety Valves.

Sensors (Basel, Switzerland)
This paper highlights the significance of safety and reliability in modern industries, particularly in sectors like petroleum and LNG, where safety valves play a critical role in ensuring system safety under extreme conditions. To enhance the reliabi...

Reproducibility of artificial intelligence-enabled plaque measurements between systolic and diastolic phases from coronary computed tomography angiography.

European radiology
OBJECTIVES: Current coronary CT angiography (CTA) guidelines suggest both end-systolic and mid-diastolic phases of the cardiac cycle can be used for CTA image acquisition. However, whether differences in the phase of the cardiac cycle influence coron...

Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence.

Eye (London, England)
BACKGROUND: Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, affecting people with diabetes. The timely diagnosis and treatment of DR are essential in preventing vision loss. Non-mydriatic fundus cameras and artificial intelligenc...

Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis.

Journal of biomedical informatics
OBJECTIVE: Large language models (LLMs) such as ChatGPT are increasingly explored in medical domains. However, the absence of standard guidelines for performance evaluation has led to methodological inconsistencies. This study aims to summarize the a...

Feasibility and validity of using deep learning to reconstruct 12-lead ECG from three‑lead signals.

Journal of electrocardiology
BACKGROUND: In the field of mobile health, portable dynamic electrocardiogram (ECG) monitoring devices often have a limited number of lead electrodes due to considerations, such as portability and battery life. This situation leads to a contradiction...

ChatGPT and Patients With Heart Failure.

Angiology
ChatGPT (Generative Pre-trained Transformer) is a large-scale language processing model, with possibilities for professional patient support in a patient-friendly way. The aim of the study was to examine the accuracy and reproducibility of ChatGPT in...

Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach.

European radiology
OBJECTIVE: This work aimed to derive a machine learning (ML) model for the differentiation between ischemic cardiomyopathy (ICM) and non-ischemic cardiomyopathy (NICM) on non-contrast cardiovascular magnetic resonance (CMR).