AIMC Topic: Machine Learning

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Using machine learning to predict the effects and consequences of mutations in proteins.

Current opinion in structural biology
Machine and deep learning approaches can leverage the increasingly available massive datasets of protein sequences, structures, and mutational effects to predict variants with improved fitness. Many different approaches are being developed, but syste...

Machine Learning Assisted Clustering of Nanoparticle Structures.

Journal of chemical information and modeling
We propose a scheme for the automatic separation (i.e., clustering) of data sets composed of several nanoparticle (NP) structures by means of Machine Learning techniques. These data sets originate from atomistic simulations, such as global optimizati...

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 ...

Development of a Machine Learning Model for Sonographic Assessment of Gestational Age.

JAMA network open
IMPORTANCE: Fetal ultrasonography is essential for confirmation of gestational age (GA), and accurate GA assessment is important for providing appropriate care throughout pregnancy and for identifying complications, including fetal growth disorders. ...

Application of Machine Learning Methods for an Analysis of E-Nose Multidimensional Signals in Wastewater Treatment.

Sensors (Basel, Switzerland)
The work represents a successful attempt to combine a gas sensors array with instrumentation (hardware), and machine learning methods as the basis for creating numerical codes (software), together constituting an electronic nose, to correct the class...

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. ...

Assessing the Role of AI-Based Smart Sensors in Smart Cities Using AHP and MOORA.

Sensors (Basel, Switzerland)
We know that in today's advanced world, artificial intelligence (AI) and machine learning (ML)-grounded methodologies are playing a very optimistic role in performing difficult and time-consuming activities very conveniently and quickly. However, for...

Novel Method for Determining Internal Combustion Engine Dysfunctions on Platform as a Service.

Sensors (Basel, Switzerland)
This article deals with a unique, new powertrain diagnostics platform at the level of a large number of EU25 inspection stations. Implemented method uses emission measurement data and additional data from significant sample of vehicles. An original t...

Application of machine learning techniques for dementia severity prediction from psychometric tests in the elderly population.

Applied neuropsychology. Adult
Previous research has shown the benefits of early detection and treatment of dementia. This detection is usually performed manually by one or more clinicians based on reports and psychometric testing. Machine learning algorithms provide an alternativ...