AIMC Topic: Reproducibility of Results

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Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks.

Dermatology (Basel, Switzerland)
BACKGROUND: The number of naevi on a person is the strongest risk factor for melanoma; however, naevus counting is highly variable due to lack of consistent methodology and lack of inter-rater agreement. Machine learning has been shown to be a valuab...

Semi-supervised learning with progressive unlabeled data excavation for label-efficient surgical workflow recognition.

Medical image analysis
Surgical workflow recognition is a fundamental task in computer-assisted surgery and a key component of various applications in operating rooms. Existing deep learning models have achieved promising results for surgical workflow recognition, heavily ...

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans.

Scientific reports
COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives of several people. Although potential vaccines are being tested and supplied around the world, it will take a long time to reach every human being, mo...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Experimental biology and medicine (Maywood, N.J.)
Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogene...

Curated Data In - Trustworthy Models Out: The Impact of Data Quality on the Reliability of Artificial Intelligence Models as Alternatives to Animal Testing.

Alternatives to laboratory animals : ATLA
New Approach Methodologies (NAMs) that employ artificial intelligence (AI) for predicting adverse effects of chemicals have generated optimistic expectations as alternatives to animal testing. However, the major underappreciated challenge in developi...

An automated method for detecting atrial fat using convolutional neural network.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Atrial Fibrillation (A-fib) is a common cardiac rhythm problem in the population these days in which irregular heartbeat leads to blood clots, heart failure, stroke, and other significant clinical complications. Researchers have found that the atrial...

4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection.

IEEE transactions on neural networks and learning systems
Due to the high availability of large-scale annotated image datasets, knowledge transfer from pretrained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with da...

Time-Frequency Representation and Convolutional Neural Network-Based Emotion Recognition.

IEEE transactions on neural networks and learning systems
Emotions composed of cognizant logical reactions toward various situations. Such mental responses stem from physiological, cognitive, and behavioral changes. Electroencephalogram (EEG) signals provide a noninvasive and nonradioactive solution for emo...

Received Signal Strength Fingerprinting-Based Indoor Location Estimation Employing Machine Learning.

Sensors (Basel, Switzerland)
The fingerprinting technique is a popular approach to reveal location of persons, instruments or devices in an indoor environment. Typically based on signal strength measurement, a power level map is created first in the learning phase to align with ...

Self-Supervised Feature Learning and Phenotyping for Assessing Age-Related Macular Degeneration Using Retinal Fundus Images.

Ophthalmology. Retina
OBJECTIVE: Diseases such as age-related macular degeneration (AMD) are classified based on human rubrics that are prone to bias. Supervised neural networks trained using human-generated labels require labor-intensive annotations and are restricted to...