AIMC Topic: Databases, Factual

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HUTNet: An Efficient Convolutional Neural Network for Handwritten Uchen Tibetan Character Recognition.

Big data
Recognition of handwritten Uchen Tibetan characters input has been considered an efficient way of acquiring mass data in the digital era. However, it still faces considerable challenges due to seriously touching letters and various morphological feat...

Readmissions after radical nephrectomy in a national cohort.

Scandinavian journal of urology
OBJECTIVE: To analyze the factors and costs associated with 30-day readmissions for patients undergoing radical nephrectomy.

Cross-task cognitive workload recognition using a dynamic residual network with attention mechanism based on neurophysiological signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Evaluation of human cognitive workload (CW) helps improve the user experience of human-centered systems. To provide a continuous estimation of the CW, we built a CW recognizer that maps human electroencephalograms (EEGs) to ...

An Accurate Deep Learning-Based System for Automatic Pill Identification: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Medication errors account for a large proportion of all medical errors. In most homes, patients take a variety of medications for a long period. However, medication errors frequently occur because patients often throw away the containers ...

Improving SWATH-MS analysis by deep-learning.

Proteomics
Data-independent acquisition (DIA) of tandem mass spectrometry spectra has emerged as a promising technology to improve coverage and quantification of proteins in complex mixtures. The success of DIA experiments is dependent on the quality of spectra...

ElectroPredictor: An Application to Predict Mayr's Electrophilicity through Implementation of an Ensemble Model Based on Machine Learning Algorithms.

Journal of chemical information and modeling
Electrophilicity () is one of the most important parameters to understand the reactivity of an organic molecule. Although the theoretical electrophilicity index (ω) has been associated with in a small homologous series, the use of to predict in a ...

Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets.

Sensors (Basel, Switzerland)
Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. ...

Multiple machine learning methods aided virtual screening of Na 1.5 inhibitors.

Journal of cellular and molecular medicine
Na 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion chan...

Reinforcement learning using Deep networks and learning accurately localizes brain tumors on MRI with very small training sets.

BMC medical imaging
BACKGROUND: Supervised deep learning in radiology suffers from notorious inherent limitations: 1) It requires large, hand-annotated data sets; (2) It is non-generalizable; and (3) It lacks explainability and intuition. It has recently been proposed t...

A System for Converting and Recovering Texts Managed as Structured Information.

Scientific reports
This paper introduces a system that incorporates several strategies based on scientific models of how the brain records and recovers memories. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architectu...