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Defining heterogeneity of epicardial functional stenosis with low coronary flow reserve by unsupervised machine learning.

Heart and vessels
Low CFR is associated with poor prognosis, whereas it is a heterogeneous condition according to the actual coronary flow, such as high resting or low hyperemic coronary flow, which should have different physiological traits and clinical implications....

Effects of gait exercise assist robot (GEAR) on subjects with chronic stroke: A randomized controlled pilot trial.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: The aim of this study was to investigate whether gait training using the Gait Exercise Assist Robot (GEAR) is more effective for improving gait ability than treadmill gait training in chronic stroke subjects.

Improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection.

Translational psychiatry
To solve major limitations in algorithms for the metabolite-based prediction of psychiatric phenotypes, a novel prediction model for depressive symptoms based on nonlinear feature selection machine learning, the Hilbert-Schmidt independence criterion...

A Concept for a Japanese Regulatory Framework for Emerging Medical Devices with Frequently Modified Behavior.

Clinical and translational science
Recent progress in the Internet of Things and artificial intelligence has made it possible to utilize the vast quantity of personal health records, clinical data, and scientific findings for prognosis, diagnosis, and therapy. These innovative technol...

Artificial intelligence-based detection of pharyngeal cancer using convolutional neural networks.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: The prognosis for pharyngeal cancer is relatively poor. It is usually diagnosed in an advanced stage. Although the recent development of narrow-band imaging (NBI) and increased awareness among endoscopists have enabled detection of superf...

DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.

Genes & genetic systems
Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with ...

Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction.

Nature communications
The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on compl...

Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study.

BMC musculoskeletal disorders
BACKGROUND: MRI scanning has revolutionized the clinical diagnosis of lumbar spinal stenosis (LSS). However, there is currently no consensus as to how best to classify MRI findings which has hampered the development of robust longitudinal epidemiolog...

Development of Invisible Sensors and a Machine-Learning-Based Recognition System Used for Early Prediction of Discontinuous Bed-Leaving Behavior Patterns.

Sensors (Basel, Switzerland)
This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recog...