Stefan Hegselmann,Georg von Arnim,Tillmann Rheude et al.
Stefan Hegselmann et al.
Electronic health records (EHRs) offer considerable potential for clinical prediction, but their complexity and heterogeneity challenge traditional machine learning. Domain-specific electronic health record foundation models trained on unla...
Digital health interventions for HIV-related sexual risk behaviors: a systematic review and network meta-analysis [0.03%]
针对与HIV相关的性行为风险的数字卫生干预措施：系统评价和网络meta分析
Jing Ji,Yun Zhang,Xingliang Zhang et al.
Jing Ji et al.
HIV-related sexual risk behaviors (e.g., condomless anal intercourse, inconsistent condom use, multiple sexual partners) remain a major driver of HIV infection globally. Digital health interventions (DHIs), ranging from SMS and mHealth to A...
Radiogenomic modeling of EGFR mutation status in brain metastases from lung adenocarcinoma: a multicenter study with biological interpretability [0.03%]
基于影像组学模型预测肺腺癌脑转移灶EGFR突变状态的多中心研究及生物标志物探索
Fuxing Deng,Xianjing Chu,Wen Shi et al.
Fuxing Deng et al.
Accurate prediction of epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma (LUAD) with brain metastases (BMs) is crucial for guiding targeted therapy. However, noninvasive and biologically interpretable tools rema...
Association of primary care telehealth with preventable healthcare utilization and care continuity among patients with chronic conditions [0.03%]
基于慢性病患者的初级保健远程医疗服务与预防性卫生服务利用和连续性的关联研究
Jiani Yu,Yiyuan Wu,Katerina Andreadis et al.
Jiani Yu et al.
Telehealth may help maintain access to care for individuals with chronic conditions, particularly during periods of disruption. This study examined the association between telehealth use and health care utilization, continuity, and quality ...
Bridging the gap from clinical to home ECG: quantifying and overcoming accuracy loss in AI-enabled single-lead ECG models [0.03%]
从临床到家庭心电图的桥梁：量化并克服单通道AI心电图模型准确性下降的问题
Chin Lin,Wei-Ting Liu,Kai-Chieh Chen et al.
Chin Lin et al.
AI-enabled electrocardiogram (ECG) models trained on 12-lead recordings may underperform on home single-lead devices due to device and context domain shift. We trained Lead-I models using 676,192 ECGs from 246,874 patients and externally va...
Explainable foundation model for dementia screening and risk stratification using retinal fundus images [0.03%]
基于眼底图像的可解释基础模型在痴呆筛查和风险分层中的应用
Changho Han,Jaewon Kim,Hyeokjong Lee et al.
Changho Han et al.
Dementia is a growing global health challenge, and early identification is essential for timely intervention. We evaluated whether foundation model-based deep learning of retinal fundus photographs can detect dementia and predict future dem...
LLM research on public biosignals data is needed to protect patients [0.03%]
对公共生物信号数据的大型语言模型研究有助于保护患者隐私
James Anibal,Jasmine Gunkel,Hannah Huth et al.
James Anibal et al.
Large language models (LLMs) have expanded the capabilities of AI and created new opportunities in medicine. To promote the development of safe and innovative digital health tools, there must be public biosignals datasets that encourage res...
Conversational artificial intelligence for pre-procedural patient preparation: implementation, validation and patient satisfaction [0.03%]
用于术前患者准备的对话式人工智能：实施、验证及患者满意度调查
Annapoorna Kini,Andriy Vengrenyuk,Derek Pineda Np et al.
Annapoorna Kini et al.
Preparing patients for cardiac catheterization requires critical but repetitive tasks. We conducted a prospective evaluation of the AI voice assistant, Sofiya, for pre-procedural calls in our center. A customized Large Language Model was tr...
Whole body CT attenuation and volume charts from routine clinical scans via LLM report filtering [0.03%]
通过LLM报告过滤进行全身CT衰减和体积图的绘制：基于常规临床扫描数据
Christian Wachinger,Bernhard Renger,Christopher Späth et al.
Christian Wachinger et al.
Interpreting quantitative CT biomarkers, such as organ volume and tissue attenuation, requires large-scale healthy reference distributions. However, creating these is challenging because clinical datasets are often heavily enriched with pat...
Yilan Wu,Ariel Yuhan Ong,Kuang Hu et al.
Yilan Wu et al.
LLMs accelerate medical information work, but speed of synthesis does not justify reliance. As T.S. Eliot asked, "Where is the knowledge we have lost in information?" Using a data-information-evidence-practice hierarchy, LLM outputs enter c...