AIMC Topic: Neural Networks, Computer

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Predicting prime editing efficiency and product purity by deep learning.

Nature biotechnology
Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here we conducted a high-throughput screen to analyze prime editing outcomes of 92,423...

Application of Neural Network in Predicting HS from an Acid Gas Removal Unit (AGRU) with Different Compositions of Solvents.

Sensors (Basel, Switzerland)
The gas sweetening process removes hydrogen sulfide (HS) in an acid gas removal unit (AGRU) to meet the gas sales' specification, known as sweet gas. Monitoring the concentration of HS in sweet gas is crucial to avoid operational and environmental is...

Neural Networks in the Design of Molecules with Affinity to Selected Protein Domains.

International journal of molecular sciences
Drug design with machine learning support can speed up new drug discoveries. While current databases of known compounds are smaller in magnitude (approximately 108), the number of small drug-like molecules is estimated to be between 1023 and 1060. Th...

A deep learning based dual encoder-decoder framework for anatomical structure segmentation in chest X-ray images.

Scientific reports
Automated multi-organ segmentation plays an essential part in the computer-aided diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the anatomical structure segmentation remains challenging due to several indistinct str...

A deep learning based method for automatic analysis of high-throughput droplet digital PCR images.

The Analyst
Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinical diagnosis. ddPCR partitions the reaction solution containing target molecules into a large number ...

High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic segmentation of the cerebral vasculature and aneurysms facilitates incidental detection of aneurysms. The assessment of aneurysm rupture risk assists with pre-operative treatment planning and enables in-silico inv...

Comparison of Artificial Neural Network and Polynomial Approximation Models for Reflectance Spectra Reconstruction.

Sensors (Basel, Switzerland)
Knowledge of surface reflection of an object is essential in many technological fields, including graphics and cultural heritage. Compared to direct multi- or hyper-spectral capturing approaches, commercial RGB cameras allow for a high resolution and...

Robust Control Based on Adaptive Neural Network for the Process of Steady Formation of Continuous Contact Force in Unmanned Aerial Manipulator.

Sensors (Basel, Switzerland)
Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM system during the formation of contact force with the target. Firstly, the dynamic model of the contact p...

Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network.

International journal of environmental research and public health
Audio features are physical features that reflect single or complex coordinated movements in the vocal organs. Hence, in speech-based automatic depression classification, it is critical to consider the relationship among audio features. Here, we prop...

Geometric Deep Learning to Identify the Critical 3D Structural Features of the Optic Nerve Head for Glaucoma Diagnosis.

American journal of ophthalmology
PURPOSE: To compare the performance of 2 relatively recent geometric deep learning techniques in diagnosing glaucoma from a single optical coherence tomographic (OCT) scan of the optic nerve head (ONH); and to identify the 3-dimensional (3D) structur...