Latest AI and machine learning research in military medicine for healthcare professionals.
Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable, and prompt method to screen for COVID-19 using easily acquirable physiological sounds. These systems have been demonstrated previously and have shown promise but lack robust analysis of their deployment in real-world ...
The utilization of unlabeled electrocardiogram (ECG) data is always a critical topic in artificial intelligence healthcare, as the manual annotation for ECG data is a time-consuming task that requires much medical expertise. The recent development of self-supervised learning, especially contrastive learning, has provided helpful inspirations to solve this problem. In this paper, a joint cross-dime...
The rapid development of deep-learning-based edge artificial intelligence applications and their data-driven nature has led to several research issues...
OBJECTIVES: Oral health is grounded in the United National (UN) 2030 Agenda for Sustainable Developement and its 17 Goals (SDGs), in particular SDG 3 ...
Clinical decision support systems (CDSS) that are developed based on artificial intelligence and machine learning (AI/ML) approaches carry transformat...
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enthusiasm for their promise in healthcare. Despite th...
Radiomics and deep learning (DL) hold transformative promise and substantial and significant advances in oncology; however, most methods have been tes...
BACKGROUND: Effective deployment of AI tools in primary health care requires the engagement of practitioners in the development and testing of these t...
Recent advances in artificial intelligence (AI) in dermatology have demonstrated the potential to improve the accuracy of skin cancer detection. These...
Recent advances in both lightweight deep learning algorithms and edge computing increasingly enable multiple model inference tasks to be conducted con...
Human monitoring applications in indoor environments depend on accurate human identification and activity recognition (HIAR). Single modality sensor s...
A precise prediction of the health status of industrial equipment is of significant importance to determine its reliability and lifespan. This predict...
The demand for telesurgery is rising rapidly, but robust evidence regarding the feasibility of its application in urology is still rare. From March to...
In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements ...
An investigation was conducted to develop an effective automated tool to deploy micro-fabricated stretchable networks of distributed sensors onto the ...
Digital health, e-health, telemedicine-this abundance of terms illustrates the scientific and technical revolution at work, made possible by high-spee...
The exponential rise in advanced software computing and low-cost hardware has broadened the horizon for the Internet of Medical Things (IoMT), interop...
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain inju...
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much atten...
Artificial intelligence systems for health care, like any other medical device, have the potential to fail. However, specific qualities of artificial ...