Latest AI and machine learning research in information technology for healthcare professionals.
Machine learning (ML) provides the ability to examine massive datasets and uncover patterns within data without relying on assumptions such as specific variable associations, linearity in relationships, or prespecified statistical interactions. However, the application of ML to healthcare data has been met with mixed results, especially when using administrative datasets such as the electronic he...
BACKGROUND: The electronic medical record (EMR) offers unique possibilities for clinical research, but some important patient attributes are not readily available due to its unstructured properties. We applied text mining using machine learning to enable automatic classification of unstructured information on smoking status from Swedish EMR data.
BACKGROUND: 5G communication technology has been applied to several fields in telemedicine, but its effectiveness, safety, and stability in remote lap...
As an important task in digital preventive healthcare management, especially in the secondary prevention stage, active medication stocking refers to t...
Large registries, administrative data, and the electronic health record (EHR) offer opportunities to identify patients with heart failure, which can b...
BACKGROUND: The interpretability of results predicted by the machine learning models is vital, especially in the critical fields like healthcare. With...
Telemedicine is the provision of healthcare-related services from a distance and is poised to move healthcare from the physician's office back into th...
BACKGROUND: With the growing adoption of the electronic health record (EHR) worldwide over the last decade, new opportunities exist for leveraging EHR...
In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years ...
In February, 2020, the European Commission published a white paper on artificial intelligence (AI) as well as an accompanying communication and report...
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the oppor...
BACKGROUND: Electronic Health Records (EHR) are the foundation of much medical research. However, analyzing the text data of EHRs directly is an chall...
With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligenc...
This paper describes the evolving role of robotics in healthcare and allied areas with special concerns relating to the management and control of the ...
BACKGROUND: Severe sepsis and septic shock are still the leading causes of death in Intensive Care Units (ICUs), and timely diagnosis is crucial for t...
By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles cou...
SNOMED CT is a comprehensive and evolving clinical reference terminology that has been widely adopted as a common vocabulary to promote interoperabili...
Individualized treatment rules (ITRs) tailor medical treatments according to patient-specific characteristics in order to optimize patient outcomes. D...
This study aims to assess the feasibility of autonomous cochlear implant (CI) fitting by adult CI recipients based on psychoacoustic self-testing and...
Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integ...