Military Medicine

Current Scenario and Future Prospects of Adverse Drug Reactions (ADRs) Monitoring and Reporting Mechanisms in the Rural Areas of India.

Pharmacovigilance (PV) deals with the detection, collection, assessment, understanding, and preventi...

Deep Learning for Epidemiologists: An Introduction to Neural Networks.

Deep learning methods are increasingly being applied to problems in medicine and health care. Howeve...

Advances and opportunities in the new digital era of telemedicine, e-health, artificial intelligence, and beyond.

Maintaining High-Touch in High-Tech Digital Health Monitoring and Multi-Omics Prognostication: Ethical, Equity, and Societal Considerations in Precision Health for Palliative Care.

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (...

Narrowing the gap: expected versus deployment performance.

OBJECTIVES: Successful model development requires both an accurate a priori understanding of future ...

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 i...

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...

Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework.

OBJECTIVE: To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis pr...

Lessons learned from translating AI from development to deployment in healthcare.

Artificial intelligence, machine learning, and deep learning in liver transplantation.

Liver transplantation (LT) is a life-saving treatment for individuals with end-stage liver disease. ...

Healthcare provider evaluation of machine learning-directed care: reactions to deployment on a randomised controlled study.

OBJECTIVES: Clinical artificial intelligence and machine learning (ML) face barriers related to impl...

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 radiolog...

Effects of interlayer reflection and interpixel interaction in diffractive optical neural networks.

Multilayer diffractive optical neural networks (DONNs) can perform machine learning (ML) tasks at th...

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 ...

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 veterin...

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 inten...

Lessons in machine learning model deployment learned from sepsis.

In three recent and related publications, researchers from Johns Hopkins University and Bayesian Hea...

A framework for the oversight and local deployment of safe and high-quality prediction models.

Artificial intelligence/machine learning models are being rapidly developed and used in clinical pra...

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...

Promoting Ethical Deployment of Artificial Intelligence and Machine Learning in Healthcare.

[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 disciplin...