EHR Sampling Interval Bias Detection and Burden of Blood Pressure Excursions: Implications for Clinical Decision Support and Model Validity in Pediatric ECMO [0.03%]
儿科ECMO临床决策支持和模型有效性的电子健康记录抽样间隔偏差检测与血压波动负担的影响
Neel Shah,Ethan Sanford,David R Busch et al.
Neel Shah et al.
Routine Electronic Health Record (EHR) blood pressure charting under-samples dynamic physiology, risking missed hemodynamic instability. This study quantifies how HER-like down-sampling changes the detection and burden of hypo- and hyperten...
AI-Based Detection of Optical Microscopic Images of Pseudomonas aeruginosa in Planktonic and Biofilm States [0.03%]
基于人工智能的游离态和生物被膜态铜绿假单胞菌光学显微镜图像检测方法
Bidisha Sengupta,Mousa Alrubayan,Manideep Kolla et al.
Bidisha Sengupta et al.
Biofilms are resistant microbial cell aggregates that pose risks to the health and food industries and produce environmental contamination. The accurate and efficient detection and prevention of biofilms are challenging and demand interdisc...
Multi-Modal Fusion of Routine Care Electronic Health Records (EHR): A Scoping Review [0.03%]
关于常规护理电子健康记录(EHR)的多模态融合：一项题录综述
Zina Ben-Miled,Jacob A Shebesh,Jing Su et al.
Zina Ben-Miled et al.
Background: Electronic health records (EHR) are now widely available in healthcare institutions to document the medical history of patients as they interact with healthcare services. In particular, routine care EHR data a...
Effect of Elevated Temperature on Physical Activity and Falls in Low-Income Older Adults Using Zero-Inflated Poisson and Graphical Models [0.03%]
高温对低收入老年人身体活动和跌倒的影响——零膨胀泊松模型和图形模型的分析
Tho Nguyen,Dahee Kim,Yingru Li et al.
Tho Nguyen et al.
High ambient temperature poses a significant public health challenge, particularly for low-income older adults (LOAs) with preexisting health and social issues and disproportionate living conditions, placing them at a vulnerable condition o...
Multimodal Brain Growth Patterns: Insights from Canonical Correlation Analysis and Deep Canonical Correlation Analysis with Auto-Encoder [0.03%]
多模态脑发育模式：典型相关分析和自动编码器深度典型相关分析的见解
Ram Sapkota,Bishal Thapaliya,Bhaskar Ray et al.
Ram Sapkota et al.
Today's advancements in neuroimaging have been pivotal in enhancing our understanding of brain development and function using various MRI techniques. This study utilizes images from T1-weighted imaging and diffusion-weighted imaging to iden...
Data Augmentation with Cross-Modal Variational Autoencoders (DACMVA) for Cancer Survival Prediction [0.03%]
基于跨模态变分自动编码器的数据增强癌症生存预测(DACMVA)
Sara Rajaram,Cassie S Mitchell
Sara Rajaram
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a no...
Availability of Physical Activity Tracking Data from Wearable Devices for Glaucoma Patients [0.03%]
可穿戴设备记录的视野缺损患者日常活动行为的可行性研究
Sonali B Bhanvadia,Leo Meller,Kian Madjedi et al.
Sonali B Bhanvadia et al.
Physical activity has been found to potentially modulate glaucoma risk, but the evidence remains inconclusive. The increasing use of wearable physical activity trackers may provide longitudinal and granular data suitable to address this iss...
SOCRAT: a Dynamic Web Toolbox for Interactive Data Processing, Analysis and Visualization [0.03%]
SOCRAT：一个用于交互式数据处理、分析和可视化的动态网络工具箱
Alexandr A Kalinin,Selvam Palanimalai,Junqi Zhu et al.
Alexandr A Kalinin et al.
Many systems for exploratory and visual data analytics require platform-dependent software installation, coding skills, and analytical expertise. The rapid advances in data-acquisition, web-based information, and communication and computati...
Feng Liu,Miguel Hernandez-Cabronero,Victor Sanchez et al.
Feng Liu et al.
With increasing utilization of medical imaging in clinical practice and the growing dimensions of data volumes generated by various medical imaging modalities, the distribution, storage, and management of digital medical image data sets req...
Kamran Kowsari,Rasoul Sali,Lubaina Ehsan et al.
Kamran Kowsari et al.
Image classification is central to the big data revolution in medicine. Improved information processing methods for diagnosis and classification of digital medical images have shown to be successful via deep learning approaches. As this fie...