Latest AI and machine learning research in information technology for healthcare professionals.
OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based screening in an Indian ROP telemedicine program and whether differences in ROP severity between neonatal care units (NCUs) identified by using AI are related to differences in oxygen-titrating...
The advancement of investigation tools and electronic health records (EHR) enables a paradigm shift from guideline-specific therapy toward patient-specific precision medicine. The multiparametric and large detailed information necessitates novel analyses to explore the insight of diseases and to aid the diagnosis, monitoring, and outcome prediction. Artificial intelligence (AI), machine learning, ...
Omics technologies offer great promises for improving our understanding of diseases. The integration and interpretation of such data pose major challe...
The use of machine learning (ML) has become prevalent in the genome engineering space, with applications ranging from predicting target site efficienc...
Real-time identification of venous thromboembolism (VTE), defined as deep vein thrombosis (DVT) and pulmonary embolism (PE), can inform a healthcare o...
In the 21 century, while some people seek to use artificial intelligence for health services delivery, others have to surrender their health rights to...
OBJECTIVE: The development of machine learning (ML) algorithms to address a variety of issues faced in clinical practice has increased rapidly. Howeve...
OBJECTIVE: In applying machine learning (ML) to electronic health record (EHR) data, many decisions must be made before any ML is applied; such prepro...
OBJECTIVE: To report the clinical validation of an innovative, artificial intelligence (AI)-powered, portable and non-invasive medical device called W...
Artificial intelligence (AI), Internet of Things (IoT), and telemedicine are deeply involved in our daily life and have also been extensively applied ...
The increasing digitalization of social life opens up new possibilities for modern health care. This article describes innovative application possibil...
OBJECTIVE: To develop a collection of concept-relationship-concept tuples to formally represent patients' care context data to inform electronic healt...
SIGNIFICANCE: Reducing the bit depth is an effective approach to lower the cost of an optical coherence tomography (OCT) imaging device and increase t...
Artificial intelligence (AI) has been widely applied in the medical field and achieved enormous milestones in helping specialists to make diagnosis an...
OBJECTIVE: The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical informati...
Social distancing with the aim of avoiding infections and pre-serve critical care capacities during the COVID-19 pandemic has been implemented in Germ...
eHealth is the use of modern information and communication technology (ICT) for trans-institutional healthcare purposes. Important subtopics of eHealt...
The paper describes the concept of the Industry 4.0 and its reflection in health care. Industry 4.0 connects intelligent production concepts with exte...
PURPOSE OF REVIEW: To highlight artificial intelligence applications in ophthalmology during the COVID-19 pandemic that can be used to: describe ocula...
Telemedicine has been used in the daily routine of dermatologists for decades. The potential advantages are especially obvious in African countries ha...