The purpose of this review is integrating and contextualizing relevant literature on the factors
influencing the adoption of AI in the healthcare industry into a comprehensive framework …

This study provides theoretical grounds for planning smart cities using multidisciplinary
approaches, offering insightful suggestions to researchers and policy-and decision-makers …

Implementation of biomarkers in sepsis and septic shock in emergency situations, remains
highly challenging. This viewpoint arose from a public–private 3-day workshop aiming to …

We consider the anticipated adoption of Artificial Intelligence (AI) in medical diagnosis. We
examine how seemingly compelling claims are tested as AI tools move into real-world …

ABSTRACT Background: Artificial Intelligence (AI) technologies have found applications
across various arenas, and Evidence-Based Management (EBMgt) is no exception …

Abstract Machine intelligence has the potential to play a significant role in diagnosing,
managing, and guiding the treatment of disease, which supports the rising demands on …

The COVID-19 pandemic and its impact opened opportunities for the utilization of big data
and artificial intelligence (AI) for pandemic planning, preparedness, and response. Big data …

In‐hospital clinical artificial intelligence (AI) encompasses learning algorithms that use real‐
time electronic medical record (EMR) data to support clinicians in making treatment …

Purpose: To present issues treating digital transformation in the health sector and highlight
the marketing dimension of this process. Design/Methodology: The article is a literature …

Objective To derive a comprehensive implementation framework for clinical AI models within
hospitals informed by existing AI frameworks and integrated with reporting standards for …