检索结果-内蒙古大学图书馆

Characterizing Emergency Department Care for Patients With Histories of Incarceration

JACEP Open 2025年第1期6卷 100022-100022页

作者： Huang, Thomas Socrates, Vimig Ovchinnikova, Polina Faustino, Isaac Kumar, Anusha Safranek, Conrad Chi, Ling Wang, Emily A. Puglisi, Lisa Wong, Ambrose H. Wang, Karen H. Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Department for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States SEICHE Center for Health and Justice Yale School of Medicine New Haven CT United States Equity Research and Innovation Center Yale School of Medicine Yale University New Haven CT United States

Objectives: Patients with a history of incarceration experience bias from health care team members, barriers to privacy, and a multitude of health care disparities. We aimed to assess care processes delivered in emergency departments (EDs) for people with histories of incarceration. Methods: We utilized a fine-tuned large language model to identify patient incarceration status from 480,374 notes from the ED setting. We compared socio-demographic characteristics, comorbidities, and care processes, including disposition, restraint use, and sedation, between individuals with and without a history of incarceration. We then conducted multivariable logistic regression to assess the independent correlation of incarceration history and management in the ED while adjusting for demographic characteristics, health behaviors, presentation, and past medical history. Results: We found 1734 unique patient encounters with a history of incarceration from a total of 177,987 encounters. Patients with history of incarceration were more likely to be male, Black, Hispanic, or other race/ethnicity, currently unemployed or disabled, and had smoking and substance use histories, compared with those without. This cohort demonstrated higher odds of elopement (OR: 3.59 [95% CI: 2.41–5.12]), leaving against medical advice (OR: 2.39 [95% CI: 1.46–3.67]), and being subjected to sedation (OR: 3.89 [95% CI: 3.19–4.70]) and restraint use (OR: 3.76 [95% CI: 3.06–4.57]). After adjusting for covariates, the association between incarceration and elopement remained significant (adjusted odds ratio: 1.65 [95% CI: 1.08–2.43]), while associations with other dispositions, restraint use, and sedation did not persist. Conclusion: This study identified differences in patient characteristics and care processes in the ED for patients with histories of incarceration and demonstrated the potential of using natural language processing in measuring care processes in populations that are largely hidden, but highly prev

关键词： artificial intelligence emergency medicine incarceration large language models quality of health care

来源：评论

学校读者我要写书评

暂无评论

data Mining and bioinformatics Approaches to Elucidate Bacterial Communities in the Extreme Environment

Data Mining and Bioinformatics Approaches to Elucidate Bacte...

引用

2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Nirwantono, Rudi Asadi, Faisal Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Bacteria are microscopic organisms that can be found in many environments. They are abundant and have many roles in our life. Studying bacteria is essential so that we can identify the bacteria that are needed for many industrial applications. However, the main problem is that majority of the bacteria are unculturable, hampering the exploration of bacteria from different environments. Metagenomics approach which employs Next Generation Sequencing technology could help study bacteria by utilizing 16S rRNA marker gene. This study aims to demonstrate data mining and bioinformatics approaches to analyze 16S rRNA sequencing data. The raw sequencing data of 16S rRNA was collected from biological database. Then, the data were trimmed, denoised, and clustered to generate Amplicon Sequence Variants (ASVs). Diversity (alpha and beta) and taxonomic analyses were then conducted to elucidate the bacterial diversity and taxonomic profile of ASVs. The results of this work showed that Shannon and PD indices in China's hot spring were higher than Singapore and the USA. Furthermore, a significant difference was observed in the PD index. The unweighted UniFrac distance also showed there was a significant difference of the bacterial communities between the three locations. In addition, the taxonomic investigation unveiled prevalent bacterial groups in the ecosystem, namely Proteobacteria, Chloroflexi, Cyanobacteria, and Crenarchaeota. The research outcomes have the potential to serve as a foundational resource for subsequent bacterial metagenomic research, particularly the hot spring environment. © 2023 IEEE.

关键词： Bacteria

来源：评论

学校读者我要写书评

暂无评论

HECLIP: Histology-Enhanced Contrastive Learning for Imputation of Transcriptomics Profiles

arXiv

引用

arXiv 2025年

作者： Wang, Qing Chen, Wen-Jie Li, Bo Su, Jing Wang, Guangyu Song, Qianqian Department of Health Outcomes and Biomedical Informatics College of Medicine University of Florida FL32611 United States School of Biological and Behavioural Sciences Queen Mary University of London LondonE1 4NS United Kingdom Department of Computer and Information Science University of Macau Macau SAR Taipa999078 China Department of Biostatistics and Health Data Science Indiana University School of Medicine IN46202 United States Center for Bioinformatics and Computational Biology Houston Methodist Research Institute TX77030 United States Department of Cardiothoracic Surgery Weill Cornell Medicine Cornell University NY United States

Histopathology, particularly hematoxylin and eosin (H&E) staining, plays a critical role in diagnosing and characterizing pathological conditions by highlighting tissue morphology. However, H&E-stained images inherently lack molecular information, requiring costly and resource-intensive methods like spatial transcriptomics to map gene expression with spatial resolution. To address these challenges, we introduce HECLIP (Histology-Enhanced Contrastive Learning for Imputation of Profiles), an innovative deep learning framework that bridges the gap between histological imaging and molecular profiling. HECLIP is specifically designed to infer gene expression profiles directly from H&E-stained images, eliminating the need for expensive spatial transcriptomics assays. HECLIP leverages an advanced image-centric contrastive loss function to optimize image representation learning, ensuring that critical morphological patterns in histology images are effectively captured and translated into accurate gene expression profiles. This design enhances the predictive power of the image modality while minimizing reliance on gene expression data. Through extensive benchmarking on publicly available datasets, HECLIP demonstrates superior performance compared to existing approaches, delivering robust and biologically meaningful predictions. Detailed ablation studies further underscore its effectiveness in extracting molecular insights from histology images. Additionally, HECLIP’s scalable and cost-efficient approach positions it as a transformative tool for both research and clinical applications, driving advancements in precision medicine. The source code for HECLIP is openly available at https://***/QSong-github/HECLIP. © 2025, CC BY-NC-ND.

关键词： Molecular imaging

来源：评论

学校读者我要写书评

暂无评论

Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

引用

Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

来源：评论

学校读者我要写书评

暂无评论

Incorporating the Knowledge Distillation to Improve the EfficientNet Transfer Learning Capability

Incorporating the Knowledge Distillation to Improve the Effi...

引用

2020 International Conference on data science and Its Applications, ICoDSA 2020

作者： Cenggoro, Tjeng Wawan Computer Science Department School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728182353

Due to the Deep Learning requirement for a large training dataset, Transfer Learning has become a central method in the field of Computer Vision, which heavily used Deep Learning. Since the adoption of transfer learning in the field, the performance of the models in computer vision is significantly upgraded. The common transfer learning practice in computer vision research is to use state-of-the-art architectures in the ImageNet dataset as the backbone network. The best performing architecture in ImageNet is currently held by EfficientNet, which is a set of architectures that were progressively grown from a baseline architecture. By observing the EfficientNet development approach, it is natural to hypothesize that the smaller EfficientNet architecture is capable to contain the knowledge of the larger architecture. This hypothesis comes from the fact that the larger EfficientNet architecture was grown from the smaller architecture. Therefore, in this study, we experimented if it is beneficial to transfer the knowledge from the larger architecture to the smaller architecture of the EfficientNet. To achieve this goal, we proposed a transfer learning method that uses Knowledge Distillation as the knowledge transfer mechanism from the larger to smaller architecture. We found that the proposed method is able to upgrade the performance of each of the EfficientNet architecture. Several smaller architectures are even able to outperform the larger architecture that was trained using the standard transfer learning method. © 2020 IEEE.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST

引用

Nature Communications 2025年第1期16卷 1-14页

作者： Gong, Yuqiao Yuan, Xin Jiao, Qiong Yu, Zhangsheng Department of Bioinformatics and Biostatistics School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai China SJTU-Yale Joint Center for Biostatistics and Data Science Organization Shanghai Jiao Tong University Shanghai China Institute of Translational Medicine Shanghai Jiao Tong University Shanghai China National Center for Translational Medicine Shanghai Jiao Tong University Shanghai China Department of Pathology Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Clinical Research Institute Shanghai Jiao Tong University School of Medicine Shanghai China

We propose HERGAST, a system for spatial structure identification and signal amplification in ultra-large-scale and ultra-high-resolution spatial transcriptomics data. To handle ultra-large spatial transcriptomics (ST) data, we consider the divide and conquer strategy and devise a Divide-Iterate-Conquer framework especially for spatial transcriptomics data analysis, which can also be adopted by other computational methods for extending to ultra-large-scale ST data analysis. To tackle the potential over-smoothing problem arising from data splitting, we construct a heterogeneous graph network to incorporate both local and global spatial relationships. In simulations, HERGAST consistently outperforms other methods across all settings with more than a 10% increase in average adjusted rand index (ARI). In real-world datasets, HERGAST’s high-precision spatial clustering identifies SPP1+ macrophages intermingled within colorectal tumors, while the enhanced gene expression signals reveal unique spatial expression patterns of key genes in breast cancer. © The Author(s) 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Hydrodynamic Analysis of Water System in Dadahup Swamp Irrigation Area 1

A Hydrodynamic Analysis of Water System in Dadahup Swamp Irr...

引用

1st International Conference on Computer science and Artificial Intelligence, ICCSAI 2021

作者： Purboseno, Sentot Suparyanto, Teddy Hidayat, Alam Ahmad Pardamean, Bens Institute of Agriculture STIPER Department of Agricultural Engineering Yogyakarta55283 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center BINUS Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Dadahup Swamp Irrigation Area (DIR) in Kapuas Regency, Central Kalimantan is developed for agricultural activities to provide food security after the pandemic. The water system consists of various channels, gates, and a flood embankment structure, which is also connected to three different rivers: Barito River, Mangkatif River, and Kapuas Mumpung River. To quantify flood risk assessments in the area, we perform a hydrodynamic analysis using the unsteady flow method via HEC-RAS software version 4.1.0. We use geometrical profiles from topography measurements and the outer boundary of the Dadahup DIR as input for the hydrologic model. Our results estimate the maximum surface water level from both cross and longitudinal sections in the channels and find that several points near the flood embankment area are prone to flood events. Our modeling approach provides a preliminary assessment for the local government to formulate a flood mitigation plan and policy in the area. © 2021 IEEE.

关键词： Rivers

来源：评论

学校读者我要写书评

暂无评论

A bioinformatics Analysis and Homology 3D Modeling of Dihydroxy-orotate-dehydrogenase of Plasmodium ovale

A Bioinformatics Analysis and Homology 3D Modeling of Dihydr...

引用

2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Nirwantono, Rudi Assidqi, Khoirunnisa Hidayat, Alam Ahmad Pebrianto Trinugroho, Joko Pardamean, Bens Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Food Biotechnology Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Departement Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

The infection of Plasmodium vivax is relatively less virulent than the deathliest Plasmodium falciparum. However, it still can lead to a fatal case and often induces recurring malaria due to dormant parasites in the liver. Thus, the research to study the drug to treat Plasmodium vivax is essential, where the enzyme dihydroorotate dehydrogenase (DHODH) has recently become a new drug target. However, the drug-enzyme interaction study has only recently been conducted in Plasmodium falciparum (pfDHODH) due to the lack of the 3D structure of enzyme DHODH from Plasmodium vivax that is crucial for the study. Therefore, this study aimed to perform the modelling study of Plasmodium vivax DHODH (PvDHODH) to create a 3D structure as a basis for drug-protein interaction study in upcoming studies. Sequence pvDHODH (Accession: SCO68359.1) was used in homology modelling using Modeller 10.2 with the crystal structure of DHODH from DHODH (Accession: 7KZY) as a template. Overall, the model generated from the homology modelling was considered a good model, and the 3D structure was close to the native state according to several parameters, including DOPE score, GA341 score, QMEAN4 value, 3D-1D score, ERRAT2 score, and ProSA score. Ramachandran plot also revealed that almost all amino acids were distributed in the desirable and allowed area (99.1%), and only 0.9% were in generously allowed regions. Superimposition of the model with the template also indicated that the model has an almost similar structure and amino acids positioning, including in the binding pocket and active site. Therefore, the model can be used for downstream analysis in drug-protein interaction studies. Nevertheless, some improvements can still be performed to upgrade the quality of the model by deleting unaligned residues on the C-terminal and realigning the residues at the doubting site. © 2023 IEEE.

关键词： Amino acids

来源：评论

学校读者我要写书评

暂无评论

Association Between Adhesive Capsulitis of the Shoulder and Subsequent Risk of Organic Erectile Dysfunction: A Population-based Cohort Analysis

引用

Bratislava Medical Journal 2025年 1-9页

作者： Hsieh, Wen-Che Huang, Yu-Han Hsu, Tzu-Ju Tsai, Fuu-Jen Hsu, Chao-Yu Department of Chinese Medicine Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan Department of Nursing Min-Hwei Junior College of Health Care Management Tainan Taiwan Management Office for Health Data Clinical Trial Research Center China Medical University Hospital Taichung Taiwan School of Chinese Medicine College of Chinese Medicine China Medical University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Division of Medical Genetics China Medical University Children’s Hospital Taichung Taiwan Department of Biotechnology and Bioinformatics Asia University Taichung Taiwan Department of Medical Education Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan Department of Artificial Intelligence and Healthcare Management Central Taiwan University of Science and Technology Taichung Taiwan Department of General Education National Chin-Yi University of Technology Taichung Taiwan

Adhesive Capsulitis of the Shoulder (ACoS) is characterized by chronic shoulder pain, and previous research has shown that patients with chronic prostatitis or chronic pelvic pain syndrome are more prone to erectile dysfunction (ED). The study aimed to determine whether ACoS, which also involves chronic pain, might contribute to the development of ED in affected men. This study used data from Taiwan’s National Health Insurance research database, identifying patients with ACoS from 2000 to 2017 and following them through 2018. A 1:1 propensity score matching was applied based on sex, age, comorbidities, medication use, and index year. The primary outcome was ED, classified as either organic or psychogenic. After performing 1:1 propensity score matching, a total of 40,146 patients were included in both the ACoS and non-ACoS cohorts. Compared to individuals without ACoS, those with ACoS demonstrated significantly elevated risks of organic ED, psychogenic ED, and overall ED, with adjusted hazard ratios of 1.76, 1.91, and 1.76, respectively. Due to the relatively low number of psychogenic ED cases, the primary focus of this study was on organic ED. Further stratified analyses revealed that patients with ACoS consistently exhibited a significantly higher risk of developing organic ED across all age groups, irrespective of comorbid conditions or medication use. ACoS is significantly associated with an increased risk of organic ED. This association highlights the potential impact of musculoskeletal disorders on sexual health, underscoring the importance of comprehensive patient care.

关键词： Adhesive capsulitis Erectile dysfunction Frozen shoulder Population-based

来源：评论

学校读者我要写书评

暂无评论

Mapping Emergency Medicine data to the Observational Medical Outcomes Partnership Common data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency data Registry

引用

JACEP Open 2025年第1期6卷 100016-100016页

作者： Cohen, Inessa Diao, Zihan Goyal, Pawan Gupta, Aarti Hawk, Kathryn Malcom, Bill Malicki, Caitlin Sharma, Dhruv Sweeney, Brian Weiner, Scott G. Venkatesh, Arjun Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Section for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States American College of Emergency Physicians Washington DC United States Department of Emergency Medicine Brigham and Women's Hospital Boston MA United States Center for Outcomes Research and Evaluation (CORE) Section of Cardiovascular Medicine Yale School of Medicine New Haven CT United States

Objectives: This study aims to conduct a gap analysis to determine the feasibility of mapping electronic health record data from the Clinical Emergency data Registry (CEDR) to the Observational Medical Outcomes Partnership Common data Model (OMOP-CDM). Methods: We employed a structured approach using a custom-built comparison matrix. This matrix facilitated the alignment of CEDR data fields with the corresponding elements in the OMOP-CDM schema. Each field was evaluated for compatibility, with categorization into 3 distinct types: direct matches, fields requiring transformation, and fields with no OMOP-CDM equivalent. The mapping process was informed by consultations with the Observational Health data sciences and Informatics community forums and was guided by existing documentation and best practices in data harmonization. We performed descriptive analyses, quantifying the extent of direct matches and identifying the specific transformations needed for each CEDR-CDM field to ensure compliance with the OMOP-CDM model. Results: Our analysis indicates a high degree of compatibility between CEDR and OMOP, with over 90% (244/269) of CEDR fields being successfully mapped. Specifically, 173 fields had direct matches, whereas 71 required transformations. Challenges identified include addressing fields unique to CEDR with no OMOP-CDM equivalent and managing the transformations required for proper alignment. Conclusion: The OMOP-CDM presents a promising framework for standardizing emergency medicine data, thereby enhancing future query automation, analytics, and cross-institutional collaboration. Despite the potential challenges in capturing unique CEDR fields and addressing necessary transformations, most emergency department data can be standardized within the OMOP-CDM, fostering broader insights and applications in research and public health. © 2024 The Author(s)

关键词： databases electronic health records emergency service informatics opioid/adverse effects quality of health care registries

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：