AIMC Topic: Datasets as Topic

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Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization.

Current opinion in ophthalmology
PURPOSE OF REVIEW: This article aims to discuss the current state of resources enabling the democratization of artificial intelligence (AI) in ophthalmology.

Transfer learning for mobile real-time face mask detection and localization.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Due to the COVID-19 pandemic, our daily habits have suddenly changed. Gatherings are forbidden and, even when it is possible to leave the home for health or work reasons, it is necessary to wear a face mask to reduce the possibility of con...

Convolutional Neural Network Models for Automatic Preoperative Severity Assessment in Unilateral Cleft Lip.

Plastic and reconstructive surgery
BACKGROUND: Despite the wide range of cleft lip morphology, consistent scales to categorize preoperative severity do not exist. Machine learning has been used to increase accuracy and efficiency in detection and rating of multiple conditions, yet it ...

3D brain glioma segmentation in MRI through integrating multiple densely connected 2D convolutional neural networks.

Journal of Zhejiang University. Science. B
To overcome the computational burden of processing three-dimensional (3D) medical scans and the lack of spatial information in two-dimensional (2D) medical scans, a novel segmentation method was proposed that integrates the segmentation results of th...

Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Reticular pseudodrusen (RPD), a key feature of age-related macular degeneration (AMD), are poorly detected by human experts on standard color fundus photography (CFP) and typically require advanced imaging modalities such as fundus autoflu...

Pretraining model for biological sequence data.

Briefings in functional genomics
With the development of high-throughput sequencing technology, biological sequence data reflecting life information becomes increasingly accessible. Particularly on the background of the COVID-19 pandemic, biological sequence data play an important r...

Synthetic data in machine learning for medicine and healthcare.

Nature biomedical engineering
The proliferation of synthetic data in artificial intelligence for medicine and healthcare raises concerns about the vulnerabilities of the software and the challenges of current policy.

TERL: classification of transposable elements by convolutional neural networks.

Briefings in bioinformatics
Transposable elements (TEs) are the most represented sequences occurring in eukaryotic genomes. Few methods provide the classification of these sequences into deeper levels, such as superfamily level, which could provide useful and detailed informati...