AIMC Topic: Neural Networks, Computer

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Development and validation of a deep learning survival model for cervical adenocarcinoma patients.

BMC bioinformatics
BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for cervical adenocarcinoma patients and process personalized survival prediction.

Generalization of vision pre-trained models for histopathology.

Scientific reports
Out-of-distribution (OOD) generalization, especially for medical setups, is a key challenge in modern machine learning which has only recently received much attention. We investigate how different convolutional pre-trained models perform on OOD test ...

Neural network based integration of assays to assess pathogenic potential.

Scientific reports
Limited data significantly hinders our capability of biothreat assessment of novel bacterial strains. Integration of data from additional sources that can provide context about the strain can address this challenge. Datasets from different sources, h...

Characteristic mango price forecasting using combined deep-learning optimization model.

PloS one
Accurate product price forecasting is helpful for scientific decision-making and precise industrial planning. As a characteristic fruit that drives regional development, mango price prediction is of great significance to several economies. However, o...

SimpleMind: An open-source software environment that adds thinking to deep neural networks.

PloS one
Deep neural networks (DNNs) detect patterns in data and have shown versatility and strong performance in many computer vision applications. However, DNNs alone are susceptible to obvious mistakes that violate simple, common sense concepts and are lim...

Learning long-term motor timing/patterns on an orthogonal basis in random neural networks.

Neural networks : the official journal of the International Neural Network Society
The ability of the brain to generate complex spatiotemporal patterns with specific timings is essential for motor learning and temporal processing. An approach that can model this function, using the spontaneous activity of a random neural network (R...

A Prediction Model Based on Gated Nonlinear Spiking Neural Systems.

International journal of neural systems
Nonlinear spiking neural P (NSNP) systems are one of neural-like membrane computing models, abstracted by nonlinear spiking mechanisms of biological neurons. NSNP systems have a nonlinear structure and can show rich nonlinear dynamics. In this paper,...

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces.

Journal of chemical information and modeling
This paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest ...

Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks.

Sensors (Basel, Switzerland)
In recent years, hand gesture recognition (HGR) technologies that use electromyography (EMG) signals have been of considerable interest in developing human-machine interfaces. Most state-of-the-art HGR approaches are based mainly on supervised machin...

An interpretable and interactive deep learning algorithm for a clinically applicable retinal fundus diagnosis system by modelling finding-disease relationship.

Scientific reports
The identification of abnormal findings manifested in retinal fundus images and diagnosis of ophthalmic diseases are essential to the management of potentially vision-threatening eye conditions. Recently, deep learning-based computer-aided diagnosis ...