AIMC Topic: Neural Networks, Computer

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An efficient approach to diagnose brain tumors through deep CNN.

Mathematical biosciences and engineering : MBE
BACKGROUND AND OBJECTIVE: Brain tumors are among the most common complications with debilitating or even death potential. Timely detection of brain tumors particularly at an early stage can lead to successful treatment of the patients. In this regard...

Explainable Deep Learning Reproduces a 'Professional Eye' on the Diagnosis of Internal Disorders in Persimmon Fruit.

Plant & cell physiology
Recent rapid progress in deep neural network techniques has allowed recognition and classification of various objects, often exceeding the performance of the human eye. In plant biology and crop sciences, some deep neural network frameworks have been...

Style transfer with variational autoencoders is a promising approach to RNA-Seq data harmonization and analysis.

Bioinformatics (Oxford, England)
MOTIVATION: The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be...

proABC-2: PRediction of AntiBody contacts v2 and its application to information-driven docking.

Bioinformatics (Oxford, England)
MOTIVATION: Monoclonal antibodies are essential tools in the contemporary therapeutic armory. Understanding how these recognize their antigen is a fundamental step in their rational design and engineering. The rising amount of publicly available data...

OPUS-TASS: a protein backbone torsion angles and secondary structure predictor based on ensemble neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Predictions of protein backbone torsion angles (ϕ and ψ) and secondary structure from sequence are crucial subproblems in protein structure prediction. With the development of deep learning approaches, their accuracies have been significa...

Heterogeneous sensing in a multifunctional soft sensor for human-robot interfaces.

Science robotics
Soft sensors have been playing a crucial role in detecting different types of physical stimuli to part or the entire body of a robot, analogous to mechanoreceptors or proprioceptors in biology. Most of the currently available soft sensors with compac...

Distinguishing Felsenstein Zone from Farris Zone Using Neural Networks.

Molecular biology and evolution
Maximum likelihood and maximum parsimony are two key methods for phylogenetic tree reconstruction. Under certain conditions, each of these two methods can perform more or less efficiently, resulting in unresolved or disputed phylogenies. We show that...

Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.

Medicine
Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversaria...

Probabilistic forecasting of surgical case duration using machine learning: model development and validation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Accurate estimations of surgical case durations can lead to the cost-effective utilization of operating rooms. We developed a novel machine learning approach, using both structured and unstructured features as input, to predict a continuou...

Deep-learning method for data association in particle tracking.

Bioinformatics (Oxford, England)
MOTIVATION: Biological studies of dynamic processes in living cells often require accurate particle tracking as a first step toward quantitative analysis. Although many particle tracking methods have been developed for this purpose, they are typicall...