Healthcare transformation

OBJECTIVE: This study aims to facilitate the creation of quality standardized nursing statements in South Korea's hospitals using algorithmic generation based on the International Classifications of Nursing Practice (ICNP) and evaluation through Large Language Models. MATERIALS AND METHODS: We algorithmically generated 15 972 statements related to acute respiratory care using 117 concepts and concept composition models of ICNP. Human reviewers, Generative Pre-trained Transformers 4...

BACKGROUND: The COVID-19 pandemic has sharpened the focus on health care safety and quality, underscoring the importance of using standardized metrics such as the International Classification of Diseases, Tenth Revision (ICD-10). In this regard, the ICD-10 cluster Y62-Y69 serves as a proxy assessment of safety and quality in health care systems, allowing researchers to evaluate medical misadventures. Thus far, extensive research and reports support the need for more attention to safety and quality in health care...

Health and risk of disease are determined by exposure to the physical, socio-economic, and political environment and to this has been added exposure to the digital environment. Our increasingly digital lives have major implications for people's health and its monitoring, as well as for prevention and care. Digital health, which encompasses the use of health applications, connected devices and artificial intelligence medical tools, is transforming medical and healthcare practices. Used properly, it could facilitate patient-centered, inter-professional and data-driven care...

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Cardiovascular disease (CVD) remains a foremost global health concern, necessitating ongoing exploration of innovative therapeutic strategies. This review surveys the latest developments in cardiovascular therapeutics, offering a comprehensive overview of emerging approaches poised to transform disease management. The examination begins by elucidating the current epidemiological landscape of CVD and the economic challenges it poses to healthcare systems. It proceeds to scrutinize the limitations of traditional therapies, emphasizing the need for progressive interventions...

Introduction In recent years, artificial intelligence (AI) in medical imaging has undergone unprecedented innovation and advancement, sparking a revolutionary transformation in healthcare. The field of radiology is particularly implicated, as clinical radiologists are expected to interpret an ever-increasing number of complex cases in record time. Machine learning software purchased by our institution is expected to help our radiologists come to a more prompt diagnosis by delivering point-of-care quantitative analysis of suspicious findings and streamlining clinical workflow...

Integrating healthcare into traffic accident prevention through predictive modeling holds immense potential. Decentralized Defense presents a transformative vision for combating cyberbullying, prioritizing user privacy, fostering a safer online environment, and offering valuable insights for both healthcare and predictive modeling applications. As cyberbullying proliferates in social media, a pressing need exists for a robust and innovative solution that ensures user safety in the cyberspace. This paper aims toward introducing the approach of merging Blockchain and Federated Learning (FL), to create a decentralized AI solutions for cyberbullying...

This comprehensive review examines the immense capacity of nanowires, nanostructures characterized by unbounded dimensions, to profoundly transform the field of biomedicine. Nanowires, which are created by combining several materials using techniques such as electrospinning and vapor deposition, possess distinct mechanical, optical, and electrical properties. As a result, they are well-suited for use in nanoscale electronic devices, drug delivery systems, chemical sensors, and other applications. The utilization of techniques such as the vapor-liquid-solid (VLS) approach and template-assisted approaches enables the achievement of precision in synthesis...

BACKGROUND: Integrating Artificial Intelligence (AI) into healthcare has transformed the landscape of patient care and healthcare delivery. Despite this, there remains a notable gap in the existing literature synthesizing the comprehensive understanding of AI's utilization in nursing care. OBJECTIVE: This systematic review aims to synthesize the available evidence to comprehensively understand the application of AI in nursing care. METHODS: Studies published between January 2019 and December 2023, identified through CINAHL Plus with Full Text, Web of Science, PubMed, and Medline, were included in this review...

BACKGROUND: The COVID-19 pandemic significantly impacted people's mental health significantly. Frontline healthcare workers (HCWs) were arguably most affected, particularly in low-to-middle-income countries like South Africa. Understanding their experiences is important to inform interventions for social and psychological support for future pandemics. AIM: This study explored the experiences of frontline HCWs in South Africa during the COVID-19 pandemic. SETTING: The sample included HCWs from various professions and health sectors who worked with COVID-19 patients across South Africa...

Evaluating the rehabilitation status of individuals with serious mental illnesses (SMI) necessitates a comprehensive analysis of multimodal data, including unstructured text records and structured diagnostic data. However, progress in the effective assessment of rehabilitation status remains limited. Our study develops a deep learning model integrating Bidirectional Encoder Representations from Transformers (BERT) and TabNet through a late fusion strategy to enhance rehabilitation prediction, including referral risk, dangerous behaviors, self-awareness, and medication adherence, in patients with SMI...

MXene-inspired two-dimensional (2D) materials like Ti3 C2 T x are widely known for their versatile properties, including surface plasmon, higher electrical conductivity, exceptional in-plane tensile strength, EMI shielding, and IR thermal properties. The MXene nanosheets coupled poly(vinylidene fluoride) (PVDF) nanofibers with d 33 ∼-26 pm V-1 are able to capture the smaller thermal fluctuation due to a superior pyroelectric coefficient of ∼130 nC m-2 K-1 with an improved (∼7 times with respect to neat PVDF nanofibers) pyroelectric current figure of merit (FOMi )...

BACKGROUND: Wearable sensors are increasingly being explored in healthcare, including in cancer care, for their potential in continuously monitoring patients. Despite their growing adoption, significant challenges remain in the quality and consistency of data collected from wearable sensors. In particular, preprocessing pipelines to clean and standardize raw data have not been fully optimized. OBJECTIVE: The aim of this study was to conduct a systematic review of preprocessing techniques employed on wearable sensor data to ensure their readiness for artificial intelligence/machine learning ("AI/ML-ready") applications...

Gynecological health remains a critical aspect of women's overall well-being, with profound implications for maternal and reproductive outcomes. This comprehensive review synthesizes the current state of knowledge on four pivotal aspects of gynecological health: preterm birth, breast cancer and cervical cancer and infertility treatment. Machine learning (ML) has emerged as a transformative technology with the potential to revolutionize gynecology and women's healthcare. The subsets of AI, namely, machine learning (ML) and deep learning (DL) methods, have aided in detecting complex patterns from huge datasets and using such patterns in making predictions...

BACKGROUND: Breastfeeding provides several positive health benefits for the newborn child, yet breastfeeding rates remain low in the United States (US). Theory-based approaches have the potential to improve breastfeeding promotion interventions. Hence, the study examined the correlates of intention to breastfeed among US pregnant women based on the multi-theory model (MTM) of health behavior change. METHODS: Using a cross-sectional design, a 36-item online survey was administered to a nationally representative sample of 315 pregnant women in the US...

Artificial intelligence (AI) chatbots, such as ChatGPT, have widely invaded all domains of human life. They have the potential to transform healthcare future. However, their effective implementation hinges on healthcare workers' (HCWs) adoption and perceptions. This study aimed to evaluate HCWs usability of ChatGPT three months post-launch in Saudi Arabia using the System Usability Scale (SUS). A total of 194 HCWs participated in the survey. Forty-seven percent were satisfied with their usage, 57 % expressed moderate to high trust in its ability to generate medical decisions...

The healthcare landscape has long been characterized by a noticeable separation between the medical and dental fields, influencing how both oral and overall health are perceived and managed today. Long ago, tooth extraction was perceived as a form of entertainment, with barber-surgeons conducting procedures in front of crowds.1 Dentistry's transformation into a profession in the mid-1800s established a separate educational path, intensifying the divergence between medical and dental healthcare.2,3 The US Surgeon General's Oral Health in America reports in 2000 and 2021 highlighted the need to close the gap between dental and medical healthcare...

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic continues to pose significant challenges to the public health sector, including that of the United Arab Emirates (UAE). The objective of this study was to assess the efficiency and accuracy of various deep-learning models in forecasting COVID-19 cases within the UAE, thereby aiding the nation's public health authorities in informed decision-making. METHODS: This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators...

Primary hypertension is a multiplex and multifactorial disease influenced by various strong components including genetics. Extensive research such as Genome-wide association studies and candidate gene studies have revealed various single nucleotide polymorphisms (SNPs) related to hypertension, providing insights into the genetic basis of the condition. This review summarizes the current status of SNP research in primary hypertension, including examples of hypertension-related SNPs, their location, function, and frequency in different populations...

PURPOSE: Healthcare providers are under pressure due to increasing and more complex demands for services. Increased pressure on budgets and human resources adds to an ever-growing problem set. Competent leaders are in demand to ensure effective and well-performing healthcare organisations that deliver balanced results and high-quality services. Researchers have made significant efforts to identify and define determining competencies for healthcare leadership. Broad terms such as competence are, however, inherently at risk of becoming too generic to add analytical value...