AIMC Topic: Neural Networks, Computer

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Optimal Enzyme-Assisted Extraction of Phenolics from Leaves of Pongamia pinnata via Response Surface Methodology and Artificial Neural Networking.

Applied biochemistry and biotechnology
This research work seeks to evaluate the impact of selected enzyme complexes on the optimised release of phenolics from leaves of Pongamia pinnata. After preliminary solvent extraction, the P. pinnata leaf extract was subjected to enzymatic treatment...

Artificial intelligence applied to magnetic resonance imaging reliably detects the presence, but not the location, of meniscus tears: a systematic review and meta-analysis.

European radiology
OBJECTIVES: To review and compare the accuracy of convolutional neural networks (CNN) for the diagnosis of meniscal tears in the current literature and analyze the decision-making processes utilized by these CNN algorithms.

Sensor-based characterization of construction and demolition waste at high occupancy densities using synthetic training data and deep learning.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Sensor-based monitoring of construction and demolition waste (CDW) streams plays an important role in recycling (RC). Extracted knowledge about the composition of a material stream helps identifying RC paths, optimizing processing plants and form the...

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks.

Journal of imaging informatics in medicine
Automated recognition of heart shunts using saline contrast transthoracic echocardiography (SC-TTE) has the potential to transform clinical practice, enabling non-experts to assess heart shunt lesions. This study aims to develop a fully automated and...

Towards an EKG for SBO: A Neural Network for Detection and Characterization of Bowel Obstruction on CT.

Journal of imaging informatics in medicine
A neural network was developed to detect and characterize bowel obstruction, a common cause of acute abdominal pain. In this retrospective study, 202 CT scans of 165 patients with bowel obstruction from March to June 2022 were included and partitione...

Stop moving: MR motion correction as an opportunity for artificial intelligence.

Magma (New York, N.Y.)
Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can seriously deteriorate the image quality. Various prospective and retrospective methods have been proposed for MRI motion correction, among which deep learning ap...

How to evaluate uncertainty estimates in machine learning for regression?

Neural networks : the official journal of the International Neural Network Society
As neural networks become more popular, the need for accompanying uncertainty estimates increases. There are currently two main approaches to test the quality of these estimates. Most methods output a density. They can be compared by evaluating their...

Performance of Fourier-based activation function in physics-informed neural networks for patient-specific cardiovascular flows.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Physics-informed neural networks (PINNs) can be used to inversely model complex physical systems by encoding the governing partial differential equations and training data into the neural network. However, neural networks a...

Protein design using structure-based residue preferences.

Nature communications
Recent developments in protein design rely on large neural networks with up to 100s of millions of parameters, yet it is unclear which residue dependencies are critical for determining protein function. Here, we show that amino acid preferences at in...