AIMC Topic: Neural Networks, Computer

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Invariance, Encodings, and Generalization: Learning Identity Effects With Neural Networks.

Neural computation
Often in language and other areas of cognition, whether two components of an object are identical or not determines if it is well formed. We call such constraints identity effects. When developing a system to learn well-formedness from examples, it i...

Double decoupled network for imbalanced obstetric intelligent diagnosis.

Mathematical biosciences and engineering : MBE
Electronic Medical Record (EMR) is the data basis of intelligent diagnosis. The diagnosis results of an EMR are multi-disease, including normal diagnosis, pathological diagnosis and complications, so intelligent diagnosis can be treated as multi-labe...

GSTCNet: Gated spatio-temporal correlation network for stroke mortality prediction.

Mathematical biosciences and engineering : MBE
Stroke continues to be the most common cause of death in China. It has great significance for mortality prediction for stroke patients, especially in terms of analyzing the complex interactions between non-negligible factors. In this paper, we presen...

SRV-GAN: A generative adversarial network for segmenting retinal vessels.

Mathematical biosciences and engineering : MBE
In the field of ophthalmology, retinal diseases are often accompanied by complications, and effective segmentation of retinal blood vessels is an important condition for judging retinal diseases. Therefore, this paper proposes a segmentation model fo...

Identifying daily activities of patient work for type 2 diabetes and co-morbidities: a deep learning and wearable camera approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: People are increasingly encouraged to self-manage their chronic conditions; however, many struggle to practise it effectively. Most studies that investigate patient work (ie, tasks involved in self-management and contexts influencing such ...

Effective drug-target interaction prediction with mutual interaction neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Accurately predicting drug-target interaction (DTI) is a crucial step to drug discovery. Recently, deep learning techniques have been widely used for DTI prediction and achieved significant performance improvement. One challenge in buildi...

Prior knowledge facilitates low homologous protein secondary structure prediction with DSM distillation.

Bioinformatics (Oxford, England)
MOTIVATION: Protein secondary structure prediction (PSSP) is one of the fundamental and challenging problems in the field of computational biology. Accurate PSSP relies on sufficient homologous protein sequences to build the multiple sequence alignme...

transferGWAS: GWAS of images using deep transfer learning.

Bioinformatics (Oxford, England)
MOTIVATION: Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide ...

Detection of weak micro-scratches on aspherical lenses using a Gabor neural network and transfer learning.

Applied optics
Surface defect detection is a crucial step in ensuring the quality of lenses. One method to check for surface defects is to use an optical system integrated with an industrial camera to magnify and highlight the position of a defect on the surface of...

Temporal convolution network with a dual attention mechanism for φ-OTDR event classification.

Applied optics
We propose a hybrid model named channel attention based temporal convolutional network combined with spatial attention and bidirectional long short-term memory network (ATCN-SA-BiLSTM) for phase sensitive optical time domain reflectometry signal reco...