AIMC Topic: Neural Networks, Computer

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Outcomes of Adversarial Attacks on Deep Learning Models for Ophthalmology Imaging Domains.

JAMA ophthalmology
This study investigates whether adversarial attacks can confuse deep learning systems based on imaging domains.

Artificial intelligence in the diagnosis, treatment and prevention of urinary stones.

Current opinion in urology
PURPOSE OF REVIEW: There has a been rapid progress in the use of artificial intelligence in all aspects of healthcare, and in urology, this is particularly astute in the overall management of urolithiasis. This article reviews advances in the use of ...

Synthetic minority oversampling of vital statistics data with generative adversarial networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extrem...

Applications of neural networks in urology: a systematic review.

Current opinion in urology
PURPOSE OF REVIEW: Over the last decade, major advancements in artificial intelligence technology have emerged and revolutionized the extent to which physicians are able to personalize treatment modalities and care for their patients. Artificial inte...

The era of artificial intelligence-based individualized telemedicine is coming.

Journal of the Chinese Medical Association : JCMA
Artificial intelligence (AI), Internet of Things (IoT), and telemedicine are deeply involved in our daily life and have also been extensively applied in the medical field, especially in ophthalmology. Clinical ophthalmologists are required to perform...

DeepCDA: deep cross-domain compound-protein affinity prediction through LSTM and convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: An essential part of drug discovery is the accurate prediction of the binding affinity of new compound-protein pairs. Most of the standard computational methods assume that compounds or proteins of the test data are observed during the tr...

Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research
BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this a...

SAINT: self-attention augmented inception-inside-inception network improves protein secondary structure prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Protein structures provide basic insight into how they can interact with other proteins, their functions and biological roles in an organism. Experimental methods (e.g. X-ray crystallography and nuclear magnetic resonance spectroscopy) fo...

[Discrimination of lung cancer and adjacent normal tissues based on permittivity by optimized probabilistic neural network].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To propose a probabilistic neural network classification method optimized by simulated annealing algorithm (SA-PNN) to discriminate lung cancer and adjacent normal tissues based on permittivity.

Red blood cell classification in lensless single random phase encoding using convolutional neural networks.

Optics express
Rapid cell identification is achieved in a compact and field-portable system employing single random phase encoding to record opto-biological signatures of living biological cells of interest. The lensless, 3D-printed system uses a diffuser to encode...