Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study [0.03%]
基于人工智能的电子健康档案数据机器学习方法，用于识别和转诊来自初级保健医生的高风险患者到眼科专家：病例对照回顾性研究
Joshua A Young,Chin-Wen Chang,Charles W Scales et al.
Joshua A Young et al.
Background: Identification and referral of at-risk patients from primary care practitioners (PCPs) to eye care professionals remain a challenge. Approximately 1.9 million Americans suffer from vision loss as a result of u...
Reidentification of Participants in Shared Clinical Data Sets: Experimental Study [0.03%]
共享临床数据集中的再识别研究：实验研究
Daniela Wiepert,Bradley A Malin,Joseph R Duffy et al.
Daniela Wiepert et al.
Background: Large curated data sets are required to leverage speech-based tools in health care. These are costly to produce, resulting in increased interest in data sharing. As speech can potentially identify speakers (ie...
Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study [0.03%]
多答案和多焦点问题的抽取式临床问答数据集开发与评估研究
Sungrim Moon,Huan He,Heling Jia et al.
Sungrim Moon et al.
Background: Extractive question-answering (EQA) is a useful natural language processing (NLP) application for answering patient-specific questions by locating answers in their clinical notes. Realistic clinical EQA can yi...
Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study [0.03%]
基于糖尿病数字预防项目的用户数字参与表型的机器学习研究：评估研究
Danissa V Rodriguez,Ji Chen,Ratnalekha V N Viswanadham et al.
Danissa V Rodriguez et al.
Background: Digital diabetes prevention programs (dDPPs) are effective "digital prescriptions" but have high attrition rates and program noncompletion. To address this, we developed a personalized automatic messaging syst...
An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study [0.03%]
医务人员及工作人员使用糖尿病人工智能预测工具的情况评估：混合研究方法研究
Winston R Liaw,Yessenia Ramos Silva,Erica G Soltero et al.
Winston R Liaw et al.
Background: Nearly one-third of patients with diabetes are poorly controlled (hemoglobin A1c≥9%). Identifying at-risk individuals and providing them with effective treatment is an important strategy for preventing poor c...
Prediction of Chronic Stress and Protective Factors in Adults: Development of an Interpretable Prediction Model Based on XGBoost and SHAP Using National Cross-sectional DEGS1 Data [0.03%]
基于XGBoost和SHAP的慢性压力及保护因素可解释预测模型的构建与验证——德国人口横断面DEGS1数据研究
Arezoo Bozorgmehr,Birgitta Weltermann
Arezoo Bozorgmehr
Background: Chronic stress is highly prevalent in the German population. It has known adverse effects on mental health, such as burnout and depression. Known long-term effects of chronic stress are cardiovascular disease,...
Assessment of ChatGPT-3.5's Knowledge in Oncology: Comparative Study with ASCO-SEP Benchmarks [0.03%]
评估ChatGPT-3.5在肿瘤学方面的知识：与ASCO-SEP基准的比较研究
Roupen Odabashian,Donald Bastin,Georden Jones et al.
Roupen Odabashian et al.
Background: ChatGPT (Open AI) is a state-of-the-art large language model that uses artificial intelligence (AI) to address questions across diverse topics. The American Society of Clinical Oncology Self-Evaluation Program...
The Impact of Expectation Management and Model Transparency on Radiologists' Trust and Utilization of AI Recommendations for Lung Nodule Assessment on Computed Tomography: Simulated Use Study [0.03%]
预期管理和模型透明度对放射科医生信任和利用人工智能建议进行计算机断层扫描肺结节评估的影响：模拟使用研究
Lotte J S Ewals,Lynn J J Heesterbeek,Bin Yu et al.
Lotte J S Ewals et al.
Background: Many promising artificial intelligence (AI) and computer-aided detection and diagnosis systems have been developed, but few have been successfully integrated into clinical practice. This is partially owing to ...
A Comparison of Personalized and Generalized Approaches to Emotion Recognition Using Consumer Wearable Devices: Machine Learning Study [0.03%]
基于消费型可穿戴设备的情绪识别研究：个性化方法与通用化方法的比较
Joe Li,Peter Washington
Joe Li
Background: There are a wide range of potential adverse health effects, ranging from headaches to cardiovascular disease, associated with long-term negative emotions and chronic stress. Because many indicators of stress a...
A Scalable Radiomics- and Natural Language Processing-Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study [0.03%]
基于放射组学和自然语言处理的机器学习管道区分胸椎脊柱骨转移痛与非痛患者的回顾性算法开发及验证研究
Hossein Naseri,Sonia Skamene,Marwan Tolba et al.
Hossein Naseri et al.
Background: The identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better management. Hence, it has the potential to improve the quality of life o...