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Biometry

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A Crossover Comparison of Standard and Telerobotic Approaches to Prenatal Sonography.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: To determine the feasibility of a telerobotic approach to remotely perform prenatal sonographic examinations.

Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Biometric measurements captured from medical devices, such as blood pressure gauges, glucose monitors, and weighing scales, are essential to tracking a patient's health. Trends in these measurements can accurately track diabetes, cardiovascular issue...

A machine learning approach to detect changes in gait parameters following a fatiguing occupational task.

Ergonomics
The purpose of this study is to provide a method for classifying non-fatigued vs. fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction ($1 Recognizer) along with the support vect...

A functional supervised learning approach to the study of blood pressure data.

Statistics in medicine
In this work, a functional supervised learning scheme is proposed for the classification of subjects into normotensive and hypertensive groups, using solely the 24-hour blood pressure data, relying on the concepts of Fréchet mean and Fréchet variance...

Impact of statistical reconstruction and compressed sensing algorithms on projection data elimination during X-ray CT image reconstruction.

Oral radiology
OBJECTIVES: To examine the effect of incomplete, or total elimination of, projection data on computed tomography (CT) images subjected to statistical reconstruction and/or compressed sensing algorithms.

Estimation and evaluation of linear individualized treatment rules to guarantee performance.

Biometrics
In clinical practice, an informative and practically useful treatment rule should be simple and transparent. However, because simple rules are likely to be far from optimal, effective methods to construct such rules must guarantee performance, in ter...

Post-boosting of classification boundary for imbalanced data using geometric mean.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel imbalance learning method for binary classes is proposed, named as Post-Boosting of classification boundary for Imbalanced data (PBI), which can significantly improve the performance of any trained neural networks (NN) classifi...

A statistical framework for biomedical literature mining.

Statistics in medicine
In systems biology, it is of great interest to identify new genes that were not previously reported to be associated with biological pathways related to various functions and diseases. Identification of these new pathway-modulating genes does not onl...

Modeling long-term human activeness using recurrent neural networks for biometric data.

BMC medical informatics and decision making
BACKGROUND: With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three ty...

A novel framework for the identification of drug target proteins: Combining stacked auto-encoders with a biased support vector machine.

PloS one
The identification of drug target proteins (IDTP) plays a critical role in biometrics. The aim of this study was to retrieve potential drug target proteins (DTPs) from a collected protein dataset, which represents an overwhelming task of great signif...