AIMC Topic: Neural Networks, Computer

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Enriching contextualized language model from knowledge graph for biomedical information extraction.

Briefings in bioinformatics
Biomedical information extraction (BioIE) is an important task. The aim is to analyze biomedical texts and extract structured information such as named entities and semantic relations between them. In recent years, pre-trained language models have la...

Different molecular enumeration influences in deep learning: an example using aqueous solubility.

Briefings in bioinformatics
Aqueous solubility is the key property driving many chemical and biological phenomena and impacts experimental and computational attempts to assess those phenomena. Accurate prediction of solubility is essential and challenging, even with modern comp...

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses.

Neural computation
Despite the fact that the loss functions of deep neural networks are highly nonconvex, gradient-based optimization algorithms converge to approximately the same performance from many random initial points. One thread of work has focused on explaining...

Noise Robust Projection Rule for Klein Hopfield Neural Networks.

Neural computation
Multistate Hopfield models, such as complex-valued Hopfield neural networks (CHNNs), have been used as multistate neural associative memories. Quaternion-valued Hopfield neural networks (QHNNs) reduce the number of weight parameters of CHNNs. The CHN...

[A preliminary investigation on a deep learning convolutional neural networks based pulmonary tuberculosis CT diagnostic model].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
To evaluate the clinical value of a pulmonary tuberculosis CT diagnostic model based on deep learning convolutional neural networks (CNN). From March 2017 to March 2018,a total of 1 764 patients with positive sputum for tuberculous bacterium and ha...

Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis.

Stem cell reports
Lineage tracing is a powerful tool in developmental biology to interrogate the evolution of tissue formation, but the dense, three-dimensional nature of tissue limits the assembly of individual cell trajectories into complete reconstructions of devel...

DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism.

Nucleic acids research
Subcellular localization of messenger RNAs (mRNAs), as a prevalent mechanism, gives precise and efficient control for the translation process. There is mounting evidence for the important roles of this process in a variety of cellular events. Computa...

Fluorescence microscopy datasets for training deep neural networks.

GigaScience
BACKGROUND: Fluorescence microscopy is an important technique in many areas of biological research. Two factors that limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging and, when ima...

MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery.

Bioinformatics (Oxford, England)
MOTIVATION: Identification of interactions between bioactive small molecules and target proteins is crucial for novel drug discovery, drug repurposing and uncovering off-target effects. Due to the tremendous size of the chemical space, experimental b...

Automated Detection of Crohn's Disease Intestinal Strictures on Capsule Endoscopy Images Using Deep Neural Networks.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Passable intestinal strictures are frequently detected on capsule endoscopy [CE]. Such strictures are a major component of inflammatory scores. Deep neural network technology for CE is emerging. However, the ability of deep neura...