Monitoring patient pathways at a secondary healthcare services through process mining via Fuzzy Miner [0.03%]
基于模糊挖掘的过程挖掘监测二级医疗服务中的患者路径
Güzin Özdağoğlu,Muhammet Damar,Fatih Safa Erenay et al.
Güzin Özdağoğlu et al.
Background: This study explored workflow pathways followed by patients seeking secondary healthcare services at a local hospital in a rural part of Turkey using process mining to improve hospital resource management. ...
Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach [0.03%]
非洲撒哈拉以南地区宫颈癌筛查接受率及其相关因素的机器学习研究
Fetlework Gubena Arage,Zinabu Bekele Tadese,Eliyas Addisu Taye et al.
Fetlework Gubena Arage et al.
Introduction: Cervical cancer, which includes squamous cell carcinoma and adenocarcinoma, is a leading cause of cancer-related deaths globally, particularly in low- and middle-income countries (LMICs). It is preventable t...
A deep learning model integrating domain-specific features for enhanced glaucoma diagnosis [0.03%]
一种结合特定领域特征的深度学习模型以提高青光眼诊断性能
Jie Xu,Erkang Jing,Yidong Chai
Jie Xu
Glaucoma is a group of serious eye diseases that can cause incurable blindness. Despite the critical need for early detection, over 60% of cases remain undiagnosed, especially in less developed regions. Glaucoma diagnosis is a costly task a...
Enhancing responses from large language models with role-playing prompts: a comparative study on answering frequently asked questions about total knee arthroplasty [0.03%]
角色扮演提示在大型语言模型回答全膝关节置换术常见问题中的应用效果研究
Yi-Chen Chen,Sheng-Hsun Lee,Huan Sheu et al.
Yi-Chen Chen et al.
Background: The application of artificial intelligence (AI) in medical education and patient interaction is rapidly growing. Large language models (LLMs) such as GPT-3.5, GPT-4, Google Gemini, and Claude 3 Opus have shown...
Psychometric properties of the Danish SDM-Q-9 questionnaire for shared decision-making in patients with pelvic floor disorders and low back pain: item response theory modelling [0.03%]
丹麦SDM-Q-9共同决策问卷在盆底功能障碍和慢性下腰痛患者中量表特征研究：项目反应理论模型分析
Mette Hulbaek,Sofie Ronja Petersen,Charlotte Ibsen
Mette Hulbaek
Background: Worldwide, involving patients in healthcare has become a focus point. Shared decision-making (SDM) is one element of patient involvement and, in many countries, including Denmark, requires culturally adapted a...
The Beacon Wiki: Mapping oncological information across the European Union [0.03%]
肿瘤信息在欧盟范围内的 beacon wiki：映射肿瘤信息全欧范围
Veronica Coppini,Giulia Ferraris,Maria Vittoria Ferrari et al.
Veronica Coppini et al.
Background: Accessing comprehensive oncological data is essential for efficient and quality healthcare delivery and research. However, obstacles, such as data fragmentation and privacy concerns which may hold back progres...
Development of a machine learning prediction model for loss to follow-up in HIV care using routine electronic medical records in a low-resource setting [0.03%]
利用常规电子病历在医疗资源匮乏地区开发HIV护理失访的机器学习预测模型
Tamrat Endebu,Girma Taye,Wakgari Deressa
Tamrat Endebu
Background: Despite the global commitment to ending AIDS by 2030, the loss of follow-up (LTFU) in HIV care remains a significant challenge. To address this issue, a data-driven clinical decision tool is crucial for identi...
Federated SPARQL query performance evaluation for exploring disease model mouse: combining gene expression, orthology, and disease knowledge graphs [0.03%]
联合查询性能评估：用于探索疾病模型小鼠的联邦SPARQL查询：结合基因表达、直向同源性和疾病知识图谱
Tatsuya Kushida,Tarcisio Mendes de Farias,Ana C Sima et al.
Tatsuya Kushida et al.
Background: The RIKEN BRC develops and maintains the RIKEN BioResource MetaDatabase to help users explore appropriate target bioresources for their experiments and prepare precise and high-quality data infrastructures. Th...
Developing a multiomics data-based mathematical model to predict colorectal cancer recurrence and metastasis [0.03%]
基于多组学数据的数学模型预测结直肠癌复发和转移
Bing Li,Ming Xiao,Rong Zeng et al.
Bing Li et al.
Background: Colorectal cancer is the fourth most deadly cancer, with a high mortality rate and a high probability of recurrence and metastasis. Since continuous examinations and disease monitoring for patients after surge...
A meta-analysis of the diagnostic test accuracy of artificial intelligence predicting emergency department dispositions [0.03%]
人工智能预测急诊科处置的诊断试验准确性Meta分析
Kuang-Ming Kuo,Chao Sheng Chang
Kuang-Ming Kuo
Background: The rapid advancement of Artificial Intelligence (AI) has led to its widespread application across various domains, showing encouraging outcomes. Many studies have utilized AI to forecast emergency department ...