AIMC Topic: Reproducibility of Results

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Artificial intelligence, machine learning, and deep learning in rhinology: a systematic review.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: This PRISMA-compliant systematic review aims to analyze the existing applications of artificial intelligence (AI), machine learning, and deep learning for rhinological purposes and compare works in terms of data pool size, AI systems, input ...

Deep learning for automated epileptiform discharge detection from scalp EEG: A systematic review.

Journal of neural engineering
Automated interictal epileptiform discharge (IED) detection has been widely studied, with machine learning methods at the forefront in recent years. As computational resources become more accessible, researchers have applied deep learning (DL) to IED...

Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications.

Diagnostic and interventional imaging
Artificial intelligence (AI) is increasingly being studied in musculoskeletal oncology imaging. AI has been applied to both primary and secondary bone tumors and assessed for various predictive tasks that include detection, segmentation, classificati...

Towards Online Ageing Detection in Transformer Oil: A Review.

Sensors (Basel, Switzerland)
Transformers play an essential role in power networks, ensuring that generated power gets to consumers at the safest voltage level. However, they are prone to insulation failure from ageing, which has fatal and economic consequences if left undetecte...

Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.

Sensors (Basel, Switzerland)
Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated to suffer from MS. Globally, a new case of MS is reported every f...

DENSEN: a convolutional neural network for estimating chronological ages from panoramic radiographs.

BMC bioinformatics
BACKGROUND: Age estimation from panoramic radiographs is a fundamental task in forensic sciences. Previous age assessment studies mainly focused on juvenile rather than elderly populations (> 25 years old). Most proposed studies were statistical or s...

Improving remote material classification ability with thermal imagery.

Scientific reports
Material recognition using optical sensors is a key enabler technology in the field of automation. Nowadays, in the age of deep learning, the challenge shifted from (manual) feature engineering to collecting big data. State of the art recognition app...

Implementation of a standardized surgical technique in robot-assisted restorative rectal cancer resection: a single center cohort study.

BMC surgery
BACKGROUND: Despite increasing focus on the technical performance of total mesorectal excision over recent decades, anastomotic leakage (AL) continues to be a serious complication for many patients, even in the hands of experienced surgical teams. Th...

Improving Misfire Fault Diagnosis with Cascading Architectures via Acoustic Vehicle Characterization.

Sensors (Basel, Switzerland)
In a world dependent on road-based transportation, it is essential to understand automobiles. We propose an acoustic road vehicle characterization system as an integrated approach for using sound captured by mobile devices to enhance transparency and...

Can deep learning reduce the time and effort required for manual segmentation in 3D reconstruction of MRI in rotator cuff tears?

PloS one
BACKGROUND/PURPOSE: The use of MRI as a diagnostic tool has gained popularity in the field of orthopedics. Although 3-dimensional (3D) MRI offers more intuitive visualization and can better facilitate treatment planning than 2-dimensional (2D) MRI, m...