AIMC Topic: Machine Learning

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Imitation and mirror systems in robots through Deep Modality Blending Networks.

Neural networks : the official journal of the International Neural Network Society
Learning to interact with the environment not only empowers the agent with manipulation capability but also generates information to facilitate building of action understanding and imitation capabilities. This seems to be a strategy adopted by biolog...

Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review.

Journal of clinical epidemiology
OBJECTIVES: Missing data is a common problem during the development, evaluation, and implementation of prediction models. Although machine learning (ML) methods are often said to be capable of circumventing missing data, it is unclear how these metho...

Machine learning to empower electrohydrodynamic processing.

Materials science & engineering. C, Materials for biological applications
Electrohydrodynamic (EHD) processes are promising healthcare fabrication technologies, as evidenced by the number of commercialised and food-and-drug administration (FDA)-approved products produced by these processes. Their ability to produce both ra...

Can we predict anti-seizure medication response in focal epilepsy using machine learning?

Clinical neurology and neurosurgery
OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning approach based on clinical factors and diffusion tensor imaging (DTI) to predict anti-seizure medication (ASM) response in focal epilepsy. We hypothesized that ASM r...

Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods.

Sensors (Basel, Switzerland)
Machine learning methods enable the electronic nose (E-Nose) for precise odor identification with both qualitative and quantitative analysis. Advanced machine learning methods are crucial for the E-Nose to gain high performance and strengthen its cap...

Cancer classification using machine learning and HRV analysis: preliminary evidence from a pilot study.

Scientific reports
Most cancer patients exhibit autonomic dysfunction with attenuated heart rate variability (HRV) levels compared to healthy controls. This research aimed to create and evaluate a machine learning (ML) model enabling discrimination between cancer patie...

Mental Health Monitoring Based on Multiperception Intelligent Wearable Devices.

Contrast media & molecular imaging
In order to improve the accuracy of the evaluation results of multiperception intelligent wearable devices, the mathematical statistical characteristics based on speech, behavior, environment, and physical signs are proposed; first, the PCA feature c...

Medical and Health Data Classification Method Based on Machine Learning.

Journal of healthcare engineering
The information defined in medical health data is researched based on machine learning-related algorithms. Also, this paper used random forest and other related algorithms to perform health data training and fitting. Research shows that the algorithm...

Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.

Computational and mathematical methods in medicine
Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the ear...

Fine-Tuning Word Embeddings for Hierarchical Representation of Data Using a Corpus and a Knowledge Base for Various Machine Learning Applications.

Computational and mathematical methods in medicine
Word embedding models have recently shown some capability to encode hierarchical information that exists in textual data. However, such models do not explicitly encode the hierarchical structure that exists among words. In this work, we propose a met...