AIMC Topic: Machine Learning

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Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Translational psychiatry
Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years reaching 1 in 68, the average age of diagnosis in the United States remains close to 4--well past the developmental window when early intervention has t...

Comparison of machine classification algorithms for fibromyalgia: neuroimages versus self-report.

The journal of pain
UNLABELLED: Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making "objective" neuroimaging...

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

International journal of geriatric psychiatry
OBJECTIVE: Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate ...

Deep neural nets as a method for quantitative structure-activity relationships.

Journal of chemical information and modeling
Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more r...

Machine learning in computational docking.

Artificial intelligence in medicine
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...

An efficient machine learning approach for diagnosis of paraquat-poisoned patients.

Computers in biology and medicine
Numerous people die of paraquat (PQ) poisoning because they were not diagnosed and treated promptly at an early stage. Till now, determination of PQ levels in blood or urine is still the only way to confirm the PQ poisoning. In order to develop a new...

Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets.

Molecular informatics
There is a growing body of evidence showing that machine learning regression results in more accurate structure-based prediction of protein-ligand binding affinity. Docking methods that aim at optimizing the affinity of ligands for a target rely on h...

Neural network operators: Constructive interpolation of multivariate functions.

Neural networks : the official journal of the International Neural Network Society
In this paper, the interpolation of multivariate data by operators of the neural network type is proved. These operators can also be used to approximate continuous functions defined on a box-domain of R(d). In order to show this fact, a uniform appro...

BagReg: Protein inference through machine learning.

Computational biology and chemistry
Protein inference from the identified peptides is of primary importance in the shotgun proteomics. The target of protein inference is to identify whether each candidate protein is truly present in the sample. To date, many computational methods have ...

Physics instruction induces changes in neural knowledge representation during successive stages of learning.

NeuroImage
Incremental instruction on the workings of a set of mechanical systems induced a progression of changes in the neural representations of the systems. The neural representations of four mechanical systems were assessed before, during, and after three ...