AIMC Topic: Humans

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Machine learning and blood pressure.

Journal of clinical hypertension (Greenwich, Conn.)
Machine learning (ML) is a type of artificial intelligence (AI) based on pattern recognition. There are different forms of supervised and unsupervised learning algorithms that are being used to identify and predict blood pressure (BP) and other measu...

The ideal couch tracking system-Requirements and evaluation of current systems.

Journal of applied clinical medical physics
INTRODUCTION: Intrafractional motion can cause substantial uncertainty in precision radiotherapy. Traditionally, the target volume is defined to be sufficiently large to cover the tumor in every position. With the robotic treatment couch, a real-time...

Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique.

Sensors (Basel, Switzerland)
We present a deep learning method used in conjunction with dual-modal microwave-ultrasound imaging to produce tomographic reconstructions of the complex-valued permittivity of numerical breast phantoms. We also assess tumor segmentation performance u...

Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques.

Preventing chronic disease
INTRODUCTION: As one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive m...

Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications
Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA acti...

Three-dimensional convolutional neural networks for simultaneous dual-tracer PET imaging.

Physics in medicine and biology
Dual-tracer positron emission tomography (PET) is a promising technique to measure the distribution of two tracers in the body by a single scan, which can improve the clinical accuracy of disease diagnosis and can also serve as a research tool for sc...

Development and verification of prediction models for preventing cardiovascular diseases.

PloS one
OBJECTIVES: Cardiovascular disease (CVD) is one of the major causes of death worldwide. For improved accuracy of CVD prediction, risk classification was performed using national time-series health examination data. The data offers an opportunity to a...

Using path signatures to predict a diagnosis of Alzheimer's disease.

PloS one
The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input p...

Distinct Mechanisms of Imagery Differentially Influence Speech Perception.

eNeuro
Neural representation can be induced without external stimulation, such as in mental imagery. Our previous study found that imagined speaking and imagined hearing modulated perceptual neural responses in opposite directions, suggesting motor-to-senso...

Otoscopic diagnosis using computer vision: An automated machine learning approach.

The Laryngoscope
OBJECTIVE: Access to otolaryngology is limited by lengthy wait lists and lack of specialists, especially in rural and remote areas. The objective of this study was to use an automated machine learning approach to build a computer vision algorithm for...