In the face of an aging population, smart healthcare services are now within reach, thanks to the proliferation of high-speed internet and other forms of digital technology. Data problems in smart healthcare, unfortunately, put artificial intelligenc...
This perspective paper explores the synergistic potential of blockchain and artificial intelligence (AI) in transforming healthcare. It begins with an overview of blockchain's role in healthcare data management, security, the pharmaceutical supply ch...
Digital therapeutics (DTx) is a recently conceived idea in health care that aims to cure ailments and modify patient behavior by employing a range of digital technologies. Notably, when traditional medication is not entirely efficacious, DTx offers a...
The Internet of Things (IoT) is an extensive system of interrelated devices equipped with sensors to monitor and track real world objects, spanning several verticals, covering many different industries. The IoT's promise is capturing interest as its ...
OBJECTIVE: Understanding and quantifying biases when designing and implementing actionable approaches to increase fairness and inclusion is critical for artificial intelligence (AI) in biomedical applications.
Artificial Intelligence (AI) holds promise in improving diagnostics and treatment. Likewise, AI is anticipated to mitigate the impacts of staff shortages in the healthcare sector. However, realising the expectations placed on AI requires a substantia...
Pflugers Archiv : European journal of physiology
Jul 6, 2024
Artificial intelligence systems (ai-systems) (e.g. machine learning, generative artificial intelligence), in healthcare and medicine, have been received with hopes of better care quality, more efficiency, lower care costs, etc. Simultaneously, these ...
Federated learning (FL) has emerged as a significant method for developing machine learning models across multiple devices without centralized data collection. Candidemia, a critical but rare disease in ICUs, poses challenges in early detection and t...
BACKGROUND: Systematic reviews (SRs) are being published at an accelerated rate. Decision-makers may struggle with comparing and choosing between multiple SRs on the same topic. We aimed to understand how healthcare decision-makers (eg, practitioners...