AIMC Topic: Neural Networks, Computer

Clear Filters Showing 29601 to 29610 of 31376 articles

Machine Learning Supports Automated Digital Image Scoring of Stool Consistency in Diapers.

Journal of pediatric gastroenterology and nutrition
BACKGROUND/AIMS: Accurate stool consistency classification of non-toilet-trained children remains challenging. This study evaluated the feasibility of automated classification of stool consistencies from diaper photos using machine learning (ML).

Long short-term memory recurrent neural network for pharmacokinetic-pharmacodynamic modeling.

International journal of clinical pharmacology and therapeutics
OBJECTIVE: Recurrent neural network (RNN) has been demonstrated as a powerful tool for analyzing various types of time series data. There is limited knowledge about the application of the RNN model in the area of pharmacokinetic (PK) and pharmacodyna...

Can a Novel Deep Neural Network Improve the Computer-Aided Detection of Solid Pulmonary Nodules and the Rate of False-Positive Findings in Comparison to an Established Machine Learning Computer-Aided Detection?

Investigative radiology
OBJECTIVE: The aim of this study was to compare the performance of 2 approved computer-aided detection (CAD) systems for detection of pulmonary solid nodules (PSNs) in an oncologic cohort. The first CAD system is based on a conventional machine learn...

Deep learning for differentiation of benign and malignant solid liver lesions on ultrasonography.

Abdominal radiology (New York)
PURPOSE: The ability to reliably distinguish benign from malignant solid liver lesions on ultrasonography can increase access, decrease costs, and help to better triage patients for biopsy. In this study, we used deep learning to differentiate benign...

Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning.

Medicine
The quality control of fetal sonographic (FS) images is essential for the correct biometric measurements and fetal anomaly diagnosis. However, quality control requires professional sonographers to perform and is often labor-intensive. To solve this p...

Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports.

Bioinformatics (Oxford, England)
MOTIVATION: The development of deep, bidirectional transformers such as Bidirectional Encoder Representations from Transformers (BERT) led to an outperformance of several Natural Language Processing (NLP) benchmarks. Especially in radiology, large am...

ToxDL: deep learning using primary structure and domain embeddings for assessing protein toxicity.

Bioinformatics (Oxford, England)
MOTIVATION: Genetically engineering food crops involves introducing proteins from other species into crop plant species or modifying already existing proteins with gene editing techniques. In addition, newly synthesized proteins can be used as therap...

A deep learning-based medication behavior monitoring system.

Mathematical biosciences and engineering : MBE
The internet of things (IoT) and deep learning are emerging technologies in diverse research fields, including the provision of IT services in medical domains. In the COVID-19 era, intelligent medication behavior monitoring systems for stable patient...

Towards peptide-based tunable multistate memristive materials.

Physical chemistry chemical physics : PCCP
Development of new memristive hardware is a technological requirement towards widespread neuromorphic computing. Molecular spintronics seems to be a fertile field for the design and preparation of this hardware. Within molecular spintronics, recent r...