AIMC Topic: Machine Learning

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Machine learning for protein folding and dynamics.

Current opinion in structural biology
Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools. The way si...

Prediction of Lower Limb Kinetics and Kinematics during Walking by a Single IMU on the Lower Back Using Machine Learning.

Sensors (Basel, Switzerland)
Recent studies have reported the application of artificial neural network (ANN) techniques on data of inertial measurement units (IMUs) to predict ground reaction forces (GRFs), which could serve as quantitative indicators of sports performance or re...

An automated 3D modeling pipeline for constructing 3D models of MONOGENEAN HARDPART using machine learning techniques.

BMC bioinformatics
BACKGROUND: Studying structural and functional morphology of small organisms such as monogenean, is difficult due to the lack of visualization in three dimensions. One possible way to resolve this visualization issue is to create digital 3D models wh...

Predicting the individual risk of psychosis conversion in at-risk mental state (ARMS): a multivariate model reveals the influence of nonpsychotic prodromal symptoms.

European child & adolescent psychiatry
To improve the prediction of the individual risk of conversion to psychosis in UHR subjects, by considering all CAARMS' symptoms at first presentation and using a multivariate machine learning method known as logistic regression with Elastic-net shri...

Development and validation of a machine learning, smartphone-based tonometer.

The British journal of ophthalmology
BACKGROUND/AIMS: To compare intraocular pressure (IOP) measurements using a prototype smartphone tonometer with other tonometers used in clinical practice.

Mitochondria Segmentation From EM Images via Hierarchical Structured Contextual Forest.

IEEE journal of biomedical and health informatics
Delineation of mitochondria from electron microscopy (EM) images is crucial to investigate its morphology and distribution, which are directly linked to neural dysfunction. However, it is a challenging task due to the varied appearances, sizes and sh...

Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets.

IEEE journal of biomedical and health informatics
Many clinical studies have revealed the high biological similarities existing among different skin pathological states. These similarities create difficulties in the efficient diagnosis of skin cancer, and encourage to study and design new intelligen...

Interpretable machine learning for predicting biomethane production in industrial-scale anaerobic co-digestion.

The Science of the total environment
The objective of this study is to apply machine learning models to accurately predict daily biomethane production in an industrial-scale co-digestion facility. The methodology involved applying elasticnet, random forest, and extreme gradient boosting...

Spectroscopy based novel spectral indices, PCA- and PLSR-coupled machine learning models for salinity stress phenotyping of rice.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Identification and development of salinity tolerant genotypes and varieties are one of the promising ways to improve productivity of salt-affected soils. Alternate methods to achieve this are required as the conventional methods are time-consuming an...