AIMC Topic: Algorithms

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Artificial Intelligence for Mental Health and Mental Illnesses: an Overview.

Current psychiatry reports
PURPOSE OF REVIEW: Artificial intelligence (AI) technology holds both great promise to transform mental healthcare and potential pitfalls. This article provides an overview of AI and current applications in healthcare, a review of recent original res...

Compositional model based on factorial evolution for realizing multi-task learning in bacterial virulent protein prediction.

Artificial intelligence in medicine
The ability of multitask learning promulgated its sovereignty in the machine learning field with the diversified application including but not limited to bioinformatics and pattern recognition. Bioinformatics provides a wide range of applications for...

Machine learning algorithm validation with a limited sample size.

PloS one
Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based data collection methods have led to a torrent of high dimensional datasets, which commonly have a small number of samples because of the intrinsic high c...

Reinforcement Learning for Improving Agent Design.

Artificial life
In many reinforcement learning tasks, the goal is to learn a policy to manipulate an agent, whose design is fixed, to maximize some notion of cumulative reward. The design of the agent's physical structure is rarely optimized for the task at hand. In...

Can Signal Delay be Functional? Including Delay in Evolved Robot Controllers.

Artificial life
Engineers, control theorists, and neuroscientists often view the delay imposed by finite signal propagation velocities as a problem that needs to be compensated for or avoided. In this article, we consider the alternative possibility that in some cas...

Classification of DNA damages on segmented comet assay images using convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Identification and quantification of DNA damage is a very significant subject in biomedical research area which still needs more robust and effective methods. One of the cheapest, easy to use and most successful method for D...

Using machine learning to predict opioid misuse among U.S. adolescents.

Preventive medicine
This study evaluated prediction performance of three different machine learning (ML) techniques in predicting opioid misuse among U.S. adolescents. Data were drawn from the 2015-2017 National Survey on Drug Use and Health (N = 41,579 adolescents, age...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Scientific reports
Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation im...

Athena: Automated Tuning of k-mer based Genomic Error Correction Algorithms using Language Models.

Scientific reports
The performance of most error-correction (EC) algorithms that operate on genomics reads is dependent on the proper choice of its configuration parameters, such as the value of k in k-mer based techniques. In this work, we target the problem of findin...