Risk Management

A randomized controlled trial of suicide prevention training for primary care providers: a study protocol.

BACKGROUND: Suicide is a national public health crisis and a critical patient safety issue. It is the 10th leading cause of death overall and the second leading cause of death among adolescents and young adults (15-34 years old). Research shows 80% of youth who died by suicide saw their primary care provider within the year of their death. It is imperative that primary care providers develop the k...

Are Current Tort Liability Doctrines Adequate for Addressing Injury Caused by AI?

As capabilities of predictive algorithms improve, machine learning will become an important element of physician practice and patient care. Implementation of artificial intelligence (AI) raises complex legal questions regarding health care professionals' and technology manufacturers' liability, particularly if they cannot explain recommendations generated by AI technology. The limited literature o...

Control of a Humanoid NAO Robot by an Adaptive Bioinspired Cerebellar Module in 3D Motion Tasks.

A bioinspired adaptive model, developed by means of a spiking neural network made of thousands of artificial neurons, has been leveraged to control a ...

Private naive bayes classification of personal biomedical data: Application in cancer data analysis.

Clinicians would benefit from access to predictive models for diagnosis, such as classification of tumors as malignant or benign, without compromising...

A Deep Neural Network-based method for estimation of 3D lifting motions.

The aim of this study is developing and validating a Deep Neural Network (DNN) based method for 3D pose estimation during lifting. The proposed DNN ba...

Distillation of the clinical algorithm improves prognosis by multi-task deep learning in high-risk Neuroblastoma.

We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep learning that incorporates a clinical algorithm, e...

Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths.

We present two approaches for the computation of hydrogen bond acceptor strengths, one by machine-learning and one by a composite quantum-mechanical p...

Cocoa flavanol effects on markers of oxidative stress and recovery after muscle damage protocol in elite rugby players.

OBJECTIVES: Strenuous exercise can impair athletic performance due to muscular inflammation and oxidative stress. Antioxidants such as cocoa flavanols...

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning.

We describe here a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and machine learning. Identifica...

Robotic hip joint testing: Development and experimental protocols.

The use of robotic systems combined with force sensing is emerging as the gold standard for in vitro biomechanical joint testing, due to the advantage...

Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's di...

Robot-Assisted Reach Training With an Active Assistant Protocol for Long-Term Upper Extremity Impairment Poststroke: A Randomized Controlled Trial.

OBJECTIVE: To assess whether robot-assisted reach training (RART) with an active assistant protocol can improve upper extremity function and kinematic...

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances.

The importance of incorporating Natural Language Processing (NLP) methods in clinical informatics research has been increasingly recognized over the p...

On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.

OBJECTIVE: Real-time myoelectric experimental protocol is considered as a means to quantify usability of myoelectric control schemes. While usability ...

Predicting Thermodynamic Properties of Alkanes by High-Throughput Force Field Simulation and Machine Learning.

Knowledge of the thermodynamic properties of molecules is essential for chemical process design and the development of new materials. Experimental mea...

Validation of a low-dose contrast 64-slice cardiac computed tomography angiography protocol for aortic valve annulus sizing.

Cardiac computed tomography angiography (CCTA) is the gold standard for accurately sizing the aortic valve annulus prior to aortic valve replacement. ...

Recognition of Sedentary Behavior by Machine Learning Analysis of Wearable Sensors during Activities of Daily Living for Telemedical Assessment of Cardiovascular Risk.

With the recent advancement in wearable computing, sensor technologies, and data processing approaches, it is possible to develop smart clothing that ...

Protocol-based state estimation for delayed Markovian jumping neural networks.

This paper is concerned with the state estimation problem for a class of Markovian jumping neural networks (MJNNs) with sensor nonlinearities, mode-de...

Multiqubit and multilevel quantum reinforcement learning with quantum technologies.

We propose a protocol to perform quantum reinforcement learning with quantum technologies. At variance with recent results on quantum reinforcement le...

Proactive expert system intervention to prevent or quit at-risk alcohol use (PRINT): study protocol of a randomized controlled trial.

BACKGROUND: The population impact of alcohol screening and brief intervention might be increased by approaching an entire population rather than indiv...