A CDE-based data structure for radiotherapeutic decision-making in breast cancer [0.03%]
一种基于CDE的乳腺癌放疗决策数据结构
Fabio Dennstädt,Maximilian Schmalfuss,Johannes Zink et al.
Fabio Dennstädt et al.
Background: The growing complexity of oncology and radiation therapy demands structured and precise data management strategies. The National Institutes of Health (NIH) have introduced Common Data Elements (CDEs) as a unif...
The impact of a patient decision aid for patients with advanced laryngeal carcinoma - a multicenter study [0.03%]
声门癌患者治疗决策辅助的效果研究——一项多中心研究
Anne N Heirman,Japke F Petersen,Abrahim Al-Mamgani et al.
Anne N Heirman et al.
Purpose: Patients with advanced larynx cancer face challenging treatment decisions. To address this, we developed and tested a patient decision aid (PDA), aiming to reduce decisional conflict (DC), and enhance knowledge a...
Exploring the possibilities and limitations of customized large language model to support and improve cervical cancer screening [0.03%]
探究定制大型语言模型支持和改善宫颈癌筛查的可能与局限性
Viola Angyal,Ádám Bertalan,Péter Domján et al.
Viola Angyal et al.
Background: The rapid advancement of artificial intelligence, driven by Generative Pre-trained Transformers (GPT), has transformed natural language processing. Prompt engineering plays a key role in guiding model outputs ...
Attention-driven hybrid deep learning and SVM model for early Alzheimer's diagnosis using neuroimaging fusion [0.03%]
基于注意力驱动的混合深度学习和SVM模型的阿尔茨海默病早期诊断方法研究及其影像组学标志物发现
Arjun Kidavunil Paduvilan,Godlin Atlas Lawrence Livingston,Sampath Kumar Kuppuchamy et al.
Arjun Kidavunil Paduvilan et al.
Alzheimer's Disease (AD) poses a significant global health challenge, necessitating early and accurate diagnosis to enable timely interventions. AD is a progressive neurodegenerative disorder that affects millions worldwide and is one of th...
Health information system in primary health care units of the Central Zone, Tigray, Northern Ethiopia [0.03%]
埃塞俄比亚北部提格雷中央区初级卫生保健单位的卫生信息系统
Letekirstos Gebreegziabher Gebretsadik,Abate Bekele Belachew,Gebregziabher Berihu Gebrekidan et al.
Letekirstos Gebreegziabher Gebretsadik et al.
Background: Health information systems require the management of health information through health management information systems and research and knowledge management. In many low-income countries, including Ethiopia, po...
AMPDECIDE amputation level patient decision aids: a feasibility study [0.03%]
截肢水平患者决策辅助(AMPDECIDE)的可行性研究
Alison W Henderson,Maryam Soltani,Bjoern D Suckow et al.
Alison W Henderson et al.
Objective: This was a feasibility study of the AMPDECIDE amputation level selection patient decision aids (one transmetatarsal vs. transtibial, the other transtibial vs. transfemoral) designed to inform a larger efficacy ...
Caroline G Watts,Kirstie G McLoughlin,Stephen Wade et al.
Caroline G Watts et al.
Background: Simulation modelling can assist with health care decision making. To inform the development and improvement of skin cancer focussed microsimulation models, we conducted a systematic review and narrative synthe...
The FAIR data point populator: collaborative FAIRification and population of FAIR data points [0.03%]
FAIR数据点填充器：协作型FAIR化及FAIR数据点填充
Daphne Wijnbergen,Rajaram Kaliyaperumal,Kees Burger et al.
Daphne Wijnbergen et al.
Background: Use of the FAIR principles (Findable, Accessible, Interoperable and Reusable) allows the rapidly growing number of biomedical datasets to be optimally (re)used. An important aspect of the FAIR principles is me...
Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques [0.03%]
基于机器学习技术预测我国中老年人快速肾功能下降风险
Yang Li,Kun Zou,Yixuan Wang et al.
Yang Li et al.
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset...
Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study [0.03%]
基于多模态数据的直肠癌预后预测多任务深度学习模型的多中心回顾性研究
Qiong Ma,Runqi Meng,Ruiting Li et al.
Qiong Ma et al.
Background: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multitask deep learning model for predicting prognosis in rectal cancer patie...