AIMC Topic: Machine Learning

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Machine learning-based heart disease diagnosis: A systematic literature review.

Artificial intelligence in medicine
Heart disease is one of the significant challenges in today's world and one of the leading causes of many deaths worldwide. Recent advancement of machine learning (ML) application demonstrates that using electrocardiogram (ECG) and patients' data, de...

Probing Diffusive Dynamics of Natural Tubule Nanoclays with Machine Learning.

ACS nano
Reproducibility of the experimental results and object of study itself is one of the basic principles in science. But what if the object characterized by technologically important properties is natural and cannot be artificially reproduced one-to-one...

Exploring Artificial Neural Networks Efficiency in Tiny Wearable Devices for Human Activity Recognition.

Sensors (Basel, Switzerland)
The increasing diffusion of tiny wearable devices and, at the same time, the advent of machine learning techniques that can perform sophisticated inference, represent a valuable opportunity for the development of pervasive computing applications. Mor...

Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods.

Sensors (Basel, Switzerland)
Linear dependence of variables is a commonly used assumption in most diagnostic systems for which many robust methodologies have been developed over the years. In case the system nonlinearities are relevant, fault diagnosis methods, relying on the as...

An adaptive synaptic array using Fowler-Nordheim dynamic analog memory.

Nature communications
In this paper we present an adaptive synaptic array that can be used to improve the energy-efficiency of training machine learning (ML) systems. The synaptic array comprises of an ensemble of analog memory elements, each of which is a micro-scale dyn...

Research on Data Analysis Network of TCM Tongue Diagnosis Based on Deep Learning Technology.

Journal of healthcare engineering
The aim of the study is to build a tongue image intelligent analysis "end-to-end" deep learning network based on a tongue diagnosis image of traditional Chinese medicine. The tongue target region in the original image was segmented by the UNet tongue...

How Machine Learning is Powering Neuroimaging to Improve Brain Health.

Neuroinformatics
This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that threaten brain health. Towards this goal, we areshar...

Utility based approach in individualized optimal dose selection using machine learning methods.

Statistics in medicine
The goal in personalized medicine is to individualize treatment using patient characteristics and improve health outcomes. Selection of optimal dose must balance the effect of dose on both treatment efficacy and toxicity outcomes. We consider a setti...

Deep learning for the dynamic prediction of multivariate longitudinal and survival data.

Statistics in medicine
The joint model for longitudinal and survival data improves time-to-event predictions by including longitudinal outcome variables in addition to baseline covariates. However, in practice, joint models may be limited by parametric assumptions in both ...

Machine learning in medical applications: A review of state-of-the-art methods.

Computers in biology and medicine
Applications of machine learning (ML) methods have been used extensively to solve various complex challenges in recent years in various application areas, such as medical, financial, environmental, marketing, security, and industrial applications. ML...