Predicting the diabetes risk by analyzing symptoms using data mining techniques [0.03%]
基于数据挖掘技术分析糖尿病风险的预测研究
Rahaf Alhamouri,Ahmad Alaiad,Dania Rahhal
Rahaf Alhamouri
Background: Diabetes is a chronic disease with a high rate of prevalence among societies, it causes detrimental effects on individuals, societies, and governments. There is an urgent need to predict the risk of developing...
Digital proficiency: a self-assessment of eHealth literacy and informatics competencies among nursing students [0.03%]
数字能力：护理专业学生进行e健康素养和卫生信息学能力的自我评估
Ahmed Loutfy,Amina Elzeiny,Corrien Van Belkum et al.
Ahmed Loutfy et al.
Background: Digital transformation in healthcare requires nurses to be proficient in digital tools for effective clinical decision-making and patient management. ...
A student-centred informatics approach for depression risk prediction using hybrid machine learning and optimization techniques to support early mental health interventions [0.03%]
一种以学生为中心的信息学方法，使用混合机器学习和优化技术进行抑郁症风险预测，以支持早期心理健康干预
Anupam Yadav,Heba Abdul-Jaleel Al-Asady,T Narmadha et al.
Anupam Yadav et al.
This study introduces a student-centred informatics framework designed to predict the risk of depression among students, with the aim of supporting early mental health interventions and personalized educational support. The framework integr...
Fuzzy logic applications in chronic disease in decision-making: a comprehensive healthcare review [0.03%]
慢性病决策中的模糊逻辑应用：全面的医疗保健综述
Sunny Thukral,Amardeep Gupta
Sunny Thukral
Diagnosis as the initial step in medical practice is one of the most significant aspects of complex clinical decision making which is convoyed by some degree of uncertainty and perplexity. With massive volumes of medical data being collecte...
Integrating artificial intelligence in physical therapy: a quasi-experimental study comparing conventional treatment with a hybrid intervention using telerehabilitation for workers with whiplash syndrome [0.03%]
人工智能在物理治疗中的应用：一项关于常规治疗与远程康复混合干预措施对挥鞭伤工人疗效的准实验研究比较
Mònica Rodríguez-Bagó,José Miguel Martínez-Martínez,Juan Carlos González González et al.
Mònica Rodríguez-Bagó et al.
Introduction: AI-assisted telerehabilitation enables remote assessment and monitoring of patient movement, improving access to treatment while reducing costs. This study aimed to compare conventional center-based physical...
AI chatbots vs. web-based learning in digital health: a randomized trial on improving dry eye syndrome knowledge for nursing students [0.03%]
人工智能聊天机器人与基于网络的学习在数字健康中的应用：一项关于改善护理专业学生干眼症知识的随机试验
Ugur Dogan,Ibrahim Edhem Yilmaz
Ugur Dogan
AI chatbots show promise for delivering interactive, personalized health education but require validation against traditional methods. This study compared effectiveness of artificial intelligence chatbot versus website-based learning for dr...
Click, care, connect: incorporating nursing informatics into undergraduate nursing curricula [0.03%]
点击、关心和联系：将护理信息学纳入本科护理课程中
Alexis Harerimana,Kristin Wicking,Narelle Biedermann et al.
Alexis Harerimana et al.
Nursing informatics is a driving force for the transformation of healthcare systems. Developing a digitally literate nursing workforce has become mandatory in many universities around the world. This study analyzed how nursing informatics w...
Péter Pál Boda,Akos Vetek
Péter Pál Boda
Parents of premature babies face extreme psychological challenges when a child is born too early - a situation for which no parents can be prepared. Parental engagement solutions, such as logging the baby's progress, can alleviate this stre...
Identifying and prioritizing the barriers and facilitators to mHealth adoption among older adults: an expert-driven best-worst method approach to inform healthcare [0.03%]
识别并优先考虑促进老年人使用移动医疗的障碍和便利因素：一种专家驱动的最佳最差方法，以推动医疗保健的发展
Betul Yildirim,Ertugrul Ayyildiz
Betul Yildirim
This study identifies and prioritizes barriers and facilitators shaping older adults' adoption of mobile health (mHealth) technologies, including apps and wearables. Using the Best-Worst Method (BWM), an expert-driven multi-criteria decisio...
AI chatbots in the PICU: parental enthusiasm contrasts with socioeconomic usage disparities [0.03%]
PICU中AI聊天机器人：父母的热情与社会经济使用的差异形成对比
R Brandon Hunter,Sriya Kakarla,Sreya Rahman et al.
R Brandon Hunter et al.
Parents of children admitted to the PICU face an overwhelming informational landscape, necessitating accessible, patient-specific information. Large Language Models (LLMs) powering AI chatbots offer a promising solution for simplifying comp...