AI Medical Compendium Topic

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A Unified Framework for Automatic Distributed Active Learning.

IEEE transactions on pattern analysis and machine intelligence
We propose a novel unified frameork for automated distributed active learning (AutoDAL) to address multiple challenging problems in active learning such as limited labeled data, imbalanced datasets, automatic hyperparameter selection as well as scala...

K-Means Clustering and Bidirectional Long- and Short-Term Neural Networks for Predicting Performance Degradation Trends of Built-In Relays in Meters.

Sensors (Basel, Switzerland)
The built-in relay in a meter is a key control component of a smart meter, and its reliability determines whether the user can use electricity safely and smoothly. In this paper, the degradation characteristics of the arc-burning energy are enhanced ...

Monocular Camera Viewpoint-Invariant Vehicular Traffic Segmentation and Classification Utilizing Small Datasets.

Sensors (Basel, Switzerland)
The work presented here develops a computer vision framework that is view angle independent for vehicle segmentation and classification from roadway traffic systems installed by the Virginia Department of Transportation (VDOT). An automated technique...

NIR spectroscopy combined with 1D-convolutional neural network for breast cancerization analysis and diagnosis.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Near-infrared (NIR) spectroscopy with deep penetration can characterize the composition of biological tissue based on the vibration of the X-H group in a rapid and high-specificity way. Deep learning is proven helpful for rapid and automatic identifi...

Assessment of the Generalization Abilities of Machine-Learning Scoring Functions for Structure-Based Virtual Screening.

Journal of chemical information and modeling
In structure-based virtual screening (SBVS), it is critical that scoring functions capture protein-ligand atomic interactions. By focusing on the local domains of ligand binding pockets, a standardized pocket Pfam-based clustering (Pfam-cluster) appr...

Flexible learning of quantum states with generative query neural networks.

Nature communications
Deep neural networks are a powerful tool for characterizing quantum states. Existing networks are typically trained with experimental data gathered from the quantum state that needs to be characterized. But is it possible to train a neural network of...

A real-time driver fatigue identification method based on GA-GRNN.

Frontiers in public health
It is of great practical and theoretical significance to identify driver fatigue state in real time and accurately and provide active safety warning in time. In this paper, a non-invasive and low-cost method of fatigue driving state identification ba...

A natural language processing approach towards harmonisation of European medicinal product information.

PloS one
Product information (PI) is a vital part of any medicinal product approved for use within the European Union and consists of a summary of products characteristics (SmPC) for healthcare professionals and package leaflet (PL) for patients, together wit...

More refined superbag: Distantly supervised relation extraction with deep clustering.

Neural networks : the official journal of the International Neural Network Society
Distant supervision (DS) can automatically generate annotated data for relation extraction (RE) with knowledge bases and corpora. The existing DS methods that train on bags selected by attention mechanism are susceptible to noisy bags and neglect use...

Unsupervised convolutional variational autoencoder deep embedding clustering for Raman spectra.

Analytical methods : advancing methods and applications
Unsupervised deep learning methods place increased emphasis on the process of cluster analysis of unknown samples without requiring sample labels. Clustering algorithms based on deep embedding networks have been recently developed and are widely used...