Latest AI and machine learning research in military medicine for healthcare professionals.
Telemedicine and online consultations with doctors has become very popular during the pandemic and involves the transmission of medical data through the internet. Thus this raises concern about the security of the medical data of the patient as the records to contain sensitive and confidential information. A Secure multimedia transformation approach is proposed in this paper using a deep learning-...
BACKGROUND: The idea of smart healthcare has gradually gained attention as a result of the information technology industry's rapid development. Smart healthcare uses next-generation technologies i.e., artificial intelligence (AI) and Internet of Things (IoT), to intelligently transform current medical methods to make them more efficient, dependable and individualized. One of the most prominent use...
Some encouraging uses for AI in medicine will lead to potentially novel legal liability issues. Complex algorithms involve an opacity that creates pro...
Rapid advances in artificial intelligence (AI) and machine learning, and specifically in deep learning (DL) techniques, have enabled broad application...
Digital transformation in medicine refers to the implementation of information technology-driven developments in the healthcare system and their impac...
Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis ...
Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of health care. With th...
Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools c...
The utilization of unlabeled electrocardiogram (ECG) data is always a critical topic in artificial intelligence healthcare, as the manual annotation f...
The rapid development of deep-learning-based edge artificial intelligence applications and their data-driven nature has led to several research issues...
Clinical decision support systems (CDSS) that are developed based on artificial intelligence and machine learning (AI/ML) approaches carry transformat...
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 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...