Military Medicine

Narrowing the gap: expected versus deployment performance.

OBJECTIVES: Successful model development requires both an accurate a priori understanding of future performance and high performance on deployment. Optimistic estimations of model performance that are unrealized in real-world clinical settings can contribute to nonuse of predictive models. This study used 2 tasks, predicting ICU mortality and Bi-Level Positive Airway Pressure failure, to quantify:...

Upper-Limb Rehabilitation of Patients with Neuromotor Deficits Using Impedance-Based Control of a 6-DOF Robot.

This paper presents a study on the use of impedance-based control of a 6-degree-of-freedom robot for upper-limb rehabilitation of patients with neuromotor deficits. The control strategy is based on impedance and does not require external force sensors at the end-effector for implementation. The experimental setup involved using the control algorithm to move the robot to a desired position, follow ...

A Deep Learning Approach for Grading of Motor Impairment Severity in Parkinson's Disease.

Objective and quantitative monitoring of movement impairments is crucial for detecting progression in neurological conditions such as Parkinson's dise...

The time is now: making the case for a UK registry of deployment of radiology artificial intelligence applications.

Artificial intelligence (AI)-based healthcare applications (apps) are rapidly evolving, and radiology is a target specialty for their implementation. ...

Content analysis of psychological first aid training manuals via topic modelling.

Psychological First Aid (PFA) is practiced worldwide. This practice in English is guided through a small collection of training manuals. Despite ubiq...

Development and deployment of interpretable machine-learning model for predicting in-hospital mortality in elderly patients with acute kidney disease.

BACKGROUND: Acute kidney injury (AKI) is more likely to develop in the elderly admitted to the intensive care unit (ICU). Acute kidney disease (AKD) a...

First, do no harm. Ethical and legal issues of artificial intelligence and machine learning in veterinary radiology and radiation oncology.

Artificial Intelligence and machine learning are novel technologies that will change the way veterinary medicine is practiced. Exactly how this change...

LTH-ECG: Lottery Ticket Hypothesis-based Deep Learning Model Compression for Atrial Fibrillation Detection from Single Lead ECG On Wearable and Implantable Devices.

Atrial Fibrillation (AF) is a kind of arrhythmia, which is a major morbidity factor, and AF can lead to stroke, heart failure and other cardiovascular...

[Problems to be solved in the development from the perspective of future application scenarios of telesurgery].

Telemedicine, which integrates medicine, communication, engineering, information and other disciplines, is a hot emerging cross field in recent years....

Competencies for the Use of Artificial Intelligence in Primary Care.

The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfi...

Digital Healthcare for Airway Diseases from Personal Environmental Exposure.

Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, h...

New Method for Surgical Diagnostics - a Robotic Telemedical Approach.

Apart from the tremendous increase in the demand for telemedicine during the COVID-19 pandemic, the use of telemedical technology offers many advantag...

Autonomous Systems and Artificial Intelligence - Hype or Prerequisite for P5 Medicine?

For meeting the challenge of aging, multi-diseased societies, cost containment, workforce development and consumerism by improved care quality and pat...

Machine Learning: The Next Paradigm Shift in Medical Education.

Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinical setting. There are a number of existing clinical...

Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.

OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluat...

Optimization of Genomic Classifiers for Clinical Deployment: Evaluation of Bayesian Optimization to Select Predictive Models of Acute Infection and In-Hospital Mortality.

Acute infection, if not rapidly and accurately detected, can lead to sepsis, organ failure and even death. Current detection of acute infection as wel...

Achieving Equitable Access to Medicines and Health Services: A COVID-19-time Recalled Matter.

In the 21 century, while some people seek to use artificial intelligence for health services delivery, others have to surrender their health rights to...

The era of artificial intelligence-based individualized telemedicine is coming.

Artificial intelligence (AI), Internet of Things (IoT), and telemedicine are deeply involved in our daily life and have also been extensively applied ...

Machine Learning Algorithm Validation: From Essentials to Advanced Applications and Implications for Regulatory Certification and Deployment.

The deployment of machine learning (ML) models in the health care domain can increase the speed and accuracy of diagnosis and improve treatment planni...

High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning.

SIGNIFICANCE: Reducing the bit depth is an effective approach to lower the cost of an optical coherence tomography (OCT) imaging device and increase t...