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Age estimation using bloodstain miRNAs based on massive parallel sequencing and machine learning: A pilot study.

Forensic science international. Genetics
Age estimation is one of the most important components in the practice of forensic science, especially for body fluids or stains at crime scenes. Recent studies have focused on the application of DNA methylation for chronological age determination in...

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

NeuroImage. Clinical
Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of ...

Stepwise Description and Outcomes of Bladder Neck Sparing Robot-Assisted Simple Prostatectomy.

Journal of endourology
To present a stepwise description and outcomes of bladder neck sparing (BNS) robot-assisted simple prostatectomy (RASP). Between March 2015 and December 2018, 30 consecutive patients with benign prostate hyperplasia underwent BNS RASP. Baseline cha...

Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification.

Sensors (Basel, Switzerland)
Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performe...

Application of a convolutional neural network for predicting the occurrence of ventricular tachyarrhythmia using heart rate variability features.

Scientific reports
Predicting the occurrence of ventricular tachyarrhythmia (VTA) in advance is a matter of utmost importance for saving the lives of cardiac arrhythmia patients. Machine learning algorithms have been used to predict the occurrence of imminent VTA. In t...

Key components of mechanical work predict outcomes in robotic stroke therapy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots...

Machine Learning Algorithms in Suicide Prevention: Clinician Interpretations as Barriers to Implementation.

The Journal of clinical psychiatry
OBJECTIVE: Machine learning algorithms in electronic medical records can classify patients by suicide risk, but no research has explored clinicians' perceptions of suicide risk flags generated by these algorithms, which may affect algorithm implement...

Deep learning for automated detection of Drosophila suzukii: potential for UAV-based monitoring.

Pest management science
BACKGROUND: The fruit fly Drosophila suzukii, or spotted wing drosophila (SWD), is a serious pest worldwide, attacking many soft-skinned fruits. An efficient monitoring system that identifies and counts SWD in crops and their surroundings is therefor...