AIMC Topic: Delivery of Health Care

Clear Filters Showing 51 to 60 of 1609 articles

XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems.

Scientific reports
The Internet of Medical Things (IoMT) has transformed healthcare delivery but faces critical challenges, including cybersecurity threats that endanger patient safety and data integrity. Intrusion Detection Systems (IDS) are essential for protecting I...

Leveraging federated learning and edge computing for pandemic-resilient healthcare.

Scientific reports
The universal demand for the development and deployment of responsive medical infrastructure and damage control techniques, including the application of technology, is the foremost necessity that emerged immediately in the post-pandemic era. Numerous...

Navigating the barriers and facilitators to implementation of AI in healthcare : a scoping review.

The bone & joint journal
AIMS: There is increasing emphasis on applying AI techniques to enhance healthcare delivery and decision-making. However, despite much interest and early promise, a major challenge is translation into clinical practice. To address the challenges of A...

[Participatory approaches in the development of AI applications in medicine: opportunities and challenges].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
The increasing integration of artificial intelligence (AI) in healthcare not only holds the potential for efficiency gains, personalized medicine, and evidence-based decisions but also raises ethical and social challenges, such as bias, lack of trans...

Exploring the social dimensions of AI integration in healthcare: a qualitative study of stakeholder views on challenges and opportunities.

BMJ open
OBJECTIVES: This study aimed to investigate the opportunities and challenges associated with integrating artificial intelligence (AI) in healthcare by exploring the perspectives of various stakeholders. The objective was to provide a nuanced understa...

[Large language models in healthcare].

Nederlands tijdschrift voor geneeskunde
Large language models, AI-based models that can generate language and which are optimized for human interaction, are widely available and also offer opportunities for healthcare. Yet, they also raise important questions about their quality and ethica...

Public Versus Academic Discourse on ChatGPT in Health Care: Mixed Methods Study.

JMIR infodemiology
BACKGROUND: The rapid emergence of artificial intelligence-based large language models (LLMs) in 2022 has initiated extensive discussions within the academic community. While proponents highlight LLMs' potential to improve writing and analytical task...

Large Language Model Architectures in Health Care: Scoping Review of Research Perspectives.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) can support health care professionals in their daily work, for example, when writing and filing reports or communicating diagnoses. With the rise of LLMs, current research investigates how LLMs could be applie...

Achieving success through ethical introduction of artificial intelligence in the healthcare ecosystem.

Healthcare management forum
Just as healthcare organizations must carefully consider how to incorporate Artificial Intelligence (AI) into patient-facing apps and messaging, so must they also think about how to ethically introduce AI into the workplace. Unreasonable expectations...

Shall we call for a doctor? How to build trust toward AI in healthcare: Insights from a Polish cross-sectional preference study.

Health policy (Amsterdam, Netherlands)
OBJECTIVES: This research aimed to investigate key success factors for the adoption of AI-driven health technologies, particularly in healthcare ecosystems of low digital literacy, such as Poland.