AIMC Topic: Algorithms

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On the effective initialisation for restricted Boltzmann machines via duality with Hopfield model.

Neural networks : the official journal of the International Neural Network Society
Restricted Boltzmann machines (RBMs) with a binary visible layer of size N and a Gaussian hidden layer of size P have been proved to be equivalent to a Hopfield neural network (HNN) made of N binary neurons and storing P patterns ΞΎ, as long as the we...

Deep learning in diabetic foot ulcers detection: A comprehensive evaluation.

Computers in biology and medicine
There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art deep learning object detecti...

Discovery of novel DGAT1 inhibitors by combination of machine learning methods, pharmacophore model and 3D-QSAR model.

Molecular diversity
DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attractive therapeutic target for obesity. Thus, development of DGAT1 inhibitors with novel chemical scaffolds is desired and important in the drug discov...

Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery.

Molecular diversity
The accumulation of massive data in the plethora of Cheminformatics databases has made the role of big data and artificial intelligence (AI) indispensable in drug design. This has necessitated the development of newer algorithms and architectures to ...

TopDomain: Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning.

Journal of chemical theory and computation
Protein domains are independent, functional, and stable structural units of proteins. Accurate protein domain boundary prediction plays an important role in understanding protein structure and evolution, as well as for protein structure prediction. C...

Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.

Journal of applied clinical medical physics
PURPOSE: In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation...

Evaluation of deep learning for COVID-19 diagnosis: Impact of image dataset organization.

Journal of applied clinical medical physics
INTRODUCTION: Coronavirus disease 2019 (COVID-19) has spread all over the world showing high transmissibility. Many studies have proposed diverse diagnostic methods based on deep learning using chest X-ray images focusing on performance improvement. ...

Artificial Intelligence Assisted Ultrasonic Extraction of Total Flavonoids from .

Molecules (Basel, Switzerland)
Flavonoids in were studied. The flavonoids in were extracted by ultrasonic method, and the extraction conditions were modeled and optimized by response the surface methodology and the artificial intelligence method. The results show that the ultras...

Epileptic Seizure Detection on an Ultra-Low-Power Embedded RISC-V Processor Using a Convolutional Neural Network.

Biosensors
The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either by drug release or electrostimulation is a highly attractive option. For such implantable medical devices, efficient and low energy consumption, smal...