AIMC Topic: Machine Learning

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A Framework for User Adaptation and Profiling for Social Robotics in Rehabilitation.

Sensors (Basel, Switzerland)
Physical rehabilitation therapies for children present a challenge, and its success-the improvement of the patient's condition-depends on many factors, such as the patient's attitude and motivation, the correct execution of the exercises prescribed b...

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

mBio
Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of isolates based on their genomic content. We applied a m...

Yield prediction with machine learning algorithms and satellite images.

Journal of the science of food and agriculture
BACKGROUND: Barley is one of the strategic agricultural products available in the world, and yield prediction is important for ensuring food security. One way of estimating a product is to use remote sensing data in conjunction with field data and me...

Assessment of and polymorphisms in age-related macular degeneration using classic and machine-learning approaches.

Ophthalmic genetics
BACKGROUND: and are pivotal genes driving increased risk for age-related macular degeneration (AMD) among several populations. Here, we performed a hospital-based case-control study to evaluate the effects of three single nucleotide polymorphisms (...

The myth of generalisability in clinical research and machine learning in health care.

The Lancet. Digital health
An emphasis on overly broad notions of generalisability as it pertains to applications of machine learning in health care can overlook situations in which machine learning might provide clinical utility. We believe that this narrow focus on generalis...

Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity.

Neural plasticity
The effects of acupuncture facilitating neural plasticity for treating diseases have been identified by clinical and experimental studies. In the last two decades, the application of neuroimaging techniques in acupuncture research provided visualized...

Importance of anthropometric features to predict physical performance in elite youth soccer: a machine learning approach.

Research in sports medicine (Print)
The present study aimed to determine the contribution of soccer players' anthropometric features to predict their physical performance. Sixteen players, from a professional youth soccer academy, were recruited. Several anthropometric features such as...

Understanding climate phenomena with data-driven models.

Studies in history and philosophy of science
In climate science, climate models are one of the main tools for understanding phenomena. Here, we develop a framework to assess the fitness of a climate model for providing understanding. The framework is based on three dimensions: representational ...

Linear predictive coding distinguishes spectral EEG features of Parkinson's disease.

Parkinsonism & related disorders
OBJECTIVE: We have developed and validated a novel EEG-based signal processing approach to distinguish PD and control patients: Linear-predictive-coding EEG Algorithm for PD (LEAPD). This method efficiently encodes EEG time series into features that ...