Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support...
3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice an...
OBJECTIVES: To develop a model for predicting biochemical recurrence (BCR) in patients with long follow-up periods using clinical parameters and the machine learning (ML) methods.
The prediction by classification of side effects incidence in a given medical treatment is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective...
Using results from genome-wide association studies for understanding complex traits is a current challenge. Here we review how genotype data can be used with different machine learning (ML) methods to predict phenotype occurrence and severity from ge...
The fingerprinting technique is a popular approach to reveal location of persons, instruments or devices in an indoor environment. Typically based on signal strength measurement, a power level map is created first in the learning phase to align with ...
Osteoporosis is a global health problem for ageing populations. The goals of osteoporosis treatment are to improve bone mineral density (BMD) and prevent fractures. One major obstacle that remains a great challenge to achieve the goals is how to sele...
INTRODUCTION: This scoping review aims to provide an overview of the existing evidence on the use of artificial intelligence (AI) and machine learning (ML) in orthodontics, its translation into clinical practice, and what limitations do exist that ha...
The purpose of this study was to propose a machine learning model and assess its ability to classify TMJ pathologies on magnetic resonance (MR) images. This retrospective cohort study included 214 TMJs from 107 patients with TMJ signs and symptoms. A...
Computational intelligence and neuroscience
Jul 5, 2021
In recent years, artificial intelligence supported by big data has gradually become more dependent on deep reinforcement learning. However, the application of deep reinforcement learning in artificial intelligence is limited by prior knowledge and mo...
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