Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
AIM: To explore the notion of post-humanism and the impact of artificial intelligence (AI) on society, nursing and healthcare. DESIGN: Discursive paper. METHODS: Critical reflection on concepts relating to post-humanism and the impact of AI, sourced from contemporary and established literature. DATA SOURCES: Information was drawn from a wide range of empirical and theoretical resources, including ...
BACKGROUND AND AIM: Artificial Intelligence (AI) has been increasingly used in cancer survivorship to support symptom management. This scoping review aimed to map existing evidence on AI applications in cancer symptom management for adult cancer survivors, including AI model development, AI-enabled intervention delivery and adoption, symptom targets, key features of the AI approaches used, reporte...
INTRODUCTION: Artificial intelligence (AI) is a branch of technology enabling machines to emulate complex human skills; it can also entail problem-sol...
INTRODUCTION: Artificial intelligence (AI) is increasingly recognized as a transformative paradigm within transplantation medicine, offering advanced ...
Artificial intelligence (AI) is rapidly advancing from automated measurement to full-report generation, yet existing frameworks do not provide a unifi...
BACKGROUND: Despite the proliferation of AI disclosure requirements in academic publishing, recent research suggests a persistent gap between policy e...
BACKGROUND: AI has the potential to transform health care in low- and middle-income countries, where access to quality care remains limited. Maternal,...
BACKGROUND: Bipolar disorder (BD) features episodic shifts among mania, hypomania, depression, mixed states, and euthymia. Timely detection of mood tr...
BACKGROUND: Widespread and sustained uptake of AI-based clinical decision support systems (CDSSs) in real-world health care settings is uncommon, desp...
To evaluate the operational impact and accuracy of a vendor-agnostic, artificial intelligence (AI)-based optical character recognition (OCR) system fo...
OBJECTIVE: To examine how algorithmic fairness is measured, operationalized, and reported in machine learning (ML) models designed to predict or suppo...
Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This rev...
BACKGROUND: Minimally invasive surgery has transformed inguinal hernia management; however, its utilization compared to open approaches remains poorly...
Societies are aging rapidly in parallel with the increasingly earlier onset of serious diseases in younger populations. These and other factors are cr...
Cerebrovascular research heavily relies on quantitative analysis of intracranial arteries from time-of-flight magnetic resonance angiography (TOF-MRA)...
Background: Endometriosis affects 10% of reproductive-aged women globally and is one of the major causes of infertility. It is a debilitating, chronic...
BACKGROUND: Large language models (LLMs) are increasingly used in health care by nonprofessionals (ie, individuals without formal training in health-r...
BACKGROUND: Deep learning (DL)-assisted low-dose computed tomography (LDCT) may improve lung cancer screening, but the available evidence is heterogen...
BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...
BACKGROUND: AI is increasingly being integrated into health care, making it important to understand stakeholder preferences for AI-enabled technologie...