检索结果-内蒙古大学图书馆

1st International Workshop on Digital Disease Detection using Social Media, DDDSM 2017, co-located with the 8th International Joint Conference on Natural Language Processing, IJCNLP 2017

作者： Warikoo, Neha Chang, Yung-Chun Hsu, Wen-Lian Institute of Biomedical Informatics National Yang-Ming University Taipei112 Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei115 Taiwan Institute of Information Science Academia Sinica Taipei115 Taiwan Graduate Institute of Data Science Taipei Medical University Taipei106 Taiwan

ISBN: (纸本)9781948087070

In this work, we introduce a novel feature engineering approach named "algebraic invariance" to identify discriminative patterns for learning relation pair features for the chemical-disease relation (CDR) task of BioCreative V. Our method exploits the existing structural similarity of the key concepts of relation descriptions from the CDR corpus to generate robust linguistic patterns for SVM tree kernel-based learning. Preprocessing of the training data classifies the entity pairs as either related or unrelated to build instance types for both inter-sentential and intra-sentential scenarios. An invariant function is proposed to process and optimally cluster similar patterns for both positive and negative instances. The learning model for CDR pairs is based on the SVM tree kernel approach, which generates feature trees and vectors and is modeled on suitable invariance based patterns, bringing brevity, precision and context to the identifier features. Results demonstrate that our method outperformed compared approaches, achieved a high recall rate of 85.08%, and averaged an F1-score of 54.34% without the use of any additional knowledge bases. © 2017 AFNLP

关键词： Forestry

来源：评论

学校读者我要写书评

暂无评论

Lung Nodule Analysis in CT Images: Deep Learning for Segmentation and Measurement 24

Lung Nodule Analysis in CT Images: Deep Learning for Segment...

引用

8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Li, Ai-Hsien Adams Aruperes, Cristian Daniel Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Division of Cardiology Far Eastern Memorial Hospital New Taipei TaiwanGraduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanGraduate Institute of Medicine Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400716874

In the realm of research, the global health challenge posed by lung cancer remains pronounced, contributing substantially to annual cancer-related fatalities. The critical imperative lies in the early identification of pulmonary nodules, frequently indicative of impending lung cancer, to enhance patient outcomes and diminish mortality rates. Computed Tomography (CT) imaging stands out as a pivotal diagnostic instrument for the timely detection of these nodules. The swift proliferation of medical imaging data has underscored the pressing necessity for precise and efficient methodologies dedicated to nodule segmentation and measurement. These approaches are crucial in assisting radiologists in their diagnostic and clinical decision-making endeavors. In this study, we introduced a thorough method for analyzing lung nodules, leveraging dataset from Far Eastern Memorial Hospital (FEMH) comprising original CT images and manually annotated ground truth masks obtained with the assistance of radiologists at FEMH. This dataset is utilized for the segmentation of nodules. We employed advanced deep learning models, specifically the U-Net architecture, identified as the optimal model through our training process. We made substantial progress in nodule segmentation, attaining an Intersection over Union (IoU) score of 0.824 and a Dice Coefficient of 0.903 for the FEMH dataset. Furthermore, our performance improved when utilizing the merged dataset comprising FEMH and Luna16, yielding an IoU score of 0.862 and a Dice Coefficient of 0.926. Luna16 has been extensively utilized in numerous studies related to nodule detection and segmentation. In the next phase of the study, the best-performing model from our segmentation phase was utilized to predict nodule masks on the merged dataset. Subsequently, we measured the size of each predicted nodule by comparing it with the size ground truth mask in millimeters. In detail, this study achieved the Pearson Correlation Coefficient (PCC) at 0.

关键词： Computerized tomography

来源：评论

学校读者我要写书评

暂无评论

Learning to predict expression efficacy of vectors in recombinant protein production

Learning to predict expression efficacy of vectors in recomb...

引用

8th Asia-Pacific Bioinformatics Conference, APBC 2010

作者： Chan, Wen-Ching Liang, Po-Huang Shih, Yan-Ping Yang, Ueng-Cheng Lin, Wen-Chang Hsu, Chun-Nan Institute of Biomedical Informatics National Yang-Ming University Taipei Taiwan Bioinformatics Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Institute of Biological Chemistry Academia Sinica Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan

Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is to fuse a target protein into different vectors in Escherichia coli (E. coli). However, the production efficacy of different vectors varies for different target proteins. Trial-and-error is still the common practice to find out the efficacy of a vector for a given target protein. Previous studies are limited in that they assumed that proteins would be over-expressed and focused only on the solubility of expressed proteins. In fact, many pairings of vectors and proteins result in no expression. Results: In this study, we applied machine learning to train prediction models to predict whether a pairing of vector-protein will express or not express in E. coli. For expressed cases, the models further predict whether the expressed proteins would be soluble. We collected a set of real cases from the clients of our recombinant protein production core facility, where six different vectors were designed and studied. This set of cases is used in both training and evaluation of our models. We evaluate three different models based on the support vector machines (SVM) and their ensembles. Unlike many previous works, these models consider the sequence of the target protein as well as the sequence of the whole fusion vector as the features. We show that a model that classifies a case into one of the three classes (no expression, inclusion body and soluble) outperforms a model that considers the nested structure of the three classes, while a model that can take advantage of the hierarchical structure of the three classes performs slight worse but comparably to the best model. Meanwhile, compared to previous works, we show that the prediction accuracy of our best method still performs the best. Lastly, we briefly present two methods to use the trained model in the design of the recombinant protein production

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

No increased risk of dementia in patients receiving androgen deprivation therapy for prostate cancer： a 5-year follow-up study

引用

Asian Journal of Andrology 2017年第4期19卷 414-417页

作者： Li-Ting Kao Herng-Ching Lin Shiu-Dong Chung Chao-Yuan Huang Graduate Institute of Life Science National Defense Medical Center Taipei 110 Taiwan China Sleep Research Center Taipei Medical University Hospital Taipei 110 Taiwan China Division of Urology Department of Surgery Far Eastern Memorial Hospital Taipei 110 Taiwan China Graduate Program in Biomedical Informatics College of Informatics Yuan Ze University Chung Li 320 Taiwan China Department of Urology National Taiwan University Hospital College of Medicine National Taiwan University Taipei 110 Taiwan China School of Public Health Taipei Medical University Taipei 110 Taiwan China

Prior studies suggested that the use of androgen deprivation therapy （ADT） in patients with prostate cancer （PC） might cause the impairment of cognitive function which is one of the common symptoms of dementia; however, the association between ADT and cognitive impairment still remains controversial. This retrospective cohort study aimed to investigate the relationship between ADT and subsequent risk of dementia using a population-based dataset, Data for this study were taken from the Taiwan （China） Longitudinal Health Insurance Database 2005. We included 755 PC patients who received ADT in the study cohort and 559 PC patients who did not receive ADT in the comparison cohort. Each patient was individually tracked for a 5-year period to define those who subsequently received a diagnosis of dementia. Results show that the incidence rates of dementia per 100 person-years were 2.35 （95% confidence interval [95% CI]： 1.82-2.98） and 1.85 （95% Ch 1.35-2.48） for PC patients who received ADT and those who did not receive ADT, respectively. The adjusted hazard ratio （HR） for dementia for PC patients who received ADT was 1.21 （95% Ch 0.82-1.78, P = 0,333） compared to those who did not receive ADT. In addition, the adjusted HRs for dementia for PC patients receiving ADT with gonadotropin-releasing hormone （GnRH） agonists and without GnRH agonists were 1.39 （95% Ch 0.80-2.40, P = 0.240） and 1.13 （95% CI： 0.75-1.71, P = 0.564）, respectively, compared to PC patients not receiving ADT. We concluded that there was no difference in the risk of subsequent dementia between PC patients who did and those who did not receive ADT.

关键词： androgen deprivation therapy dementia epidemiology prostate cancer

来源：评论

学校读者我要写书评

暂无评论

Organizational Benefits of Computerized Physician Order Entry (CPOE) System in Pakistan

Organizational Benefits of Computerized Physician Order Entr...

引用

International Conference on Platform Technology and Service (PlatCon)

作者： Suleman Atique Yen-Liang Lee Chien-Yeh Hsu Shabbir Syed-Abdul Hsiao-Hsien Rau Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei TW Master program in global health and development National Taipei University of Nursing and Health Sciences Taipei TW

Electronic prescribing i.e. e-prescribing is also known as Computerized Physician Order Entry (CPOE). It is a computer-aided system which offers the health professionals a robust platform for entering the prescription, recommended-tests, suggestions, etc. for the patients electronically rather than manually. Due to paucity of below- normal healthcare infrastructure and facilities in Pakistan which are available around the world in this modern world, there is an observable overburden on the health professionals and practitioners. Computerized Physician order entry (CPOE) system has shown to be very effective in minimizing the medication errors. Majority of the health professionals are of the view that CPOE is beneficial for both patient as well as health professionals themselves. They have shown a great deal of interest in the adoption of this new technology oriented system in our healthcare system. The results state clearly that this system is equally beneficial for organizations who want to adopt this system as perceived by the health professionals. Overall it supports the idea of adoption and implementation of CPOE in healthcare facilities in both public and private healthcare institutes. CPOE must be adopted to ease the healthcare system for patients as well as support healthcare professionals.

关键词： Medical services Organizations biomedical informatics Market research Information management Writing

来源：评论

学校读者我要写书评

暂无评论

Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

引用

8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Association of Fine Motor Loss and Allodynia in Fibromyalgia: An fNIRS Study (vol 50, pg 664, 2017)

引用

JOURNAL OF MOTOR BEHAVIOR 2018年第6期50卷 X-X页

作者： Eken, A. Gokcay, D. Yilmas, C. Baskak, B. Baltaci, A. Kara, M. Biomedical Engineering Department Düzce University Düzce Turkey Medical Informatics Department Informatics Institute Middle East Technical University Ankara Turkey Neuroscience Graduate Program Bilkent University Ankara Turkey Department of Psychiatry Ankara University Faculty of Medicine Ankara Turkey Ankara University Brain Research Center Ankara Turkey Department of Physical and Rehabilitation Medicine Yenimahalle Research Hospital Yıldırım Beyazıt University Ankara Turkey Department of Physical and Rehabilitation Medicine Hacettepe University Medical School Ankara Turkey

Recent studies showed that fine motor control dysfunction was observed in fibromyalgia (FM) syndrome as well as allodynia. However, brain signatures of this association still remain unclear. In this study, finger tapping task (FTT) and median nerve stimulation (MNS) were applied to both hands of 15 FM patients and healthy controls (HC) to understand this relationship. Hemodynamic activity was measured simultaneously using functional near-infrared spectroscopy (fNIRS). Experiments were analyzed separately by using 2x2 repeated measures ANOVA. Results for the FTT experiment revealed that HC showed higher activity than FM patients in bilateral superior parietal gyrus (SPG), left supramarginal gyrus (SMG) and right somatosensory cortex (SI). Furthermore, right-hand FTT resulted in higher activity than left-hand FTT in left SPG, left SI and right motor cortex (MI). In the MNS experiment, FM patients showed higher activity than HC in bilateral SPG, right SMG, right SI and right middle frontal gyrus (MFG). Negative correlation was observed in left SPG between FTT and MNS activities. Besides, MNS activity in left SPG was negatively correlated with left-hand pain *** study revealed that left SPG might be an important indicator to associate fine motor loss and allodynia in FM.

关键词： fNIRS Fibromyalgia Fine Motor Loss

来源：评论

学校读者我要写书评

暂无评论

CaGEDA: A web application for the integrated analysis of global gene expression patterns in cancer

引用

Applied Bioinformatics 2004年第1期3卷 49-62页

作者： Patel, Satish Lyons-Weiler, James University of Pittsburgh Cancer Institute University of Pittsburgh Medical School Pittsburgh PA United States Department of Pathology University of Pittsburgh Medical School Pittsburgh PA United States Cancer Biomarkers Laboratory University of Pittsburgh Medical School Pittsburgh PA United States Center for Pathology Informatics University of Pittsburgh Medical School Pittsburgh PA United States Benedum Center for Oncology Informatics University of Pittsburgh Medical School Pittsburgh PA United States Center for Biomedical Informatics University of Pittsburgh Medical School Pittsburgh PA United States Interdisciplinary Biomedical Graduate Program University of Pittsburgh Medical School Pittsburgh PA United States UPCI Benedum Oncology Informatics Center 304 Cancer Pavilion Pittsburgh PA 15232 5150 Centre Avenue United States

The explosion of microarray data from pilot studies, basic research and large-scale clinical trials requires the development of integrative computational tools that can not only analyse gene expression patterns but that can also evaluate the methods of analysis adopted and then provide a boost to post-analysis translational interpretation of those patterns. We have developed a web application called caGEDA (cancer gene expression data analyzer) that can: (1) upload gene expression profiles from cDNA or oligonucleotide microarrays;(2) conduct a diverse range of serial linear normalisations;(3) identify differentially expressed genes using a variety of tests - either threshold or permutation tests;(4) produce tables of literature references to papers reporting that specific genes (identified by accession numbers) are up- or down-regulated in specific cancers;(5) estimate the error of sample class prediction using the significant gene set for features;(6) perform low-bias and accurate validated learning using three computational validation techniques (leave-one-out validation, k-fold validation, random resampling validation);and (7) validate a classifier with a randomly selected or user-defined validation set. Significant genes are reported in a table of links to entries in the following databases: LocusLink, Genome View, UCSC, Ensembl, UniGene, dbSNP, AmiGO and OMIM. caGEDA is seamlessly integrated via embedded forms with UCSD's (University of California at San Diego) 2HAPI server (for medical subject heading (MeSH) term exploration) and EZ-Retrieve (to identify common transcription factors located upstream of sets of genes that exhibit similar modes of differential expression). caGEDA offers a variety of previously described and novel tests for differentially expressed genes, most notably the permutation percentile separability test, which is most appropriate for identifying genes that are significantly differentially expressed in a subset of patients. caGEDA, which

关键词： Cancer Genomics Microarray analysis

来源：评论

学校读者我要写书评

暂无评论

A new implementation method of the reverse engineering algorithm to elucidate gene functional dependencies

IEEJ Transactions on Electronics, Information and Systems

引用

IEEJ Transactions on Electronics, Information and Systems 2007年第10期127卷 1712-1718+32页

作者： Inaoka, Hidenori Fukuoka, Yutaka Ueno, Akinori Kohane, Isaac S. Institute of Biomaterials and Biomedical Engineering Tokyo Medical and Dental University 2-3-10 Kanda-Surugadai Chiyoda-ku Tokyo 101-0062 Japan School of Biomedical Science Tokyo Medical and Dental University 1-5-45 Yushima Bunkyo-ku Tokyo 113-8510 Japan Graduate School of Science and Engineering Tokyo Denki University Ishizaka Hatoyama-Cho Hiki-Gun Saitama 350-0394 Japan Informatics Program Childrens's Hospital Harvard Medical School Boston MA United States

Various clustering methods are applied to characterizing gene expression data from DNA microarrays. However, to elucidate functional dependencies of genes analysis of their associations is important. The REVerse Engineering ALgorithm (REVEAL) was developed for analyzing the functional dependencies. Although the algorithm has been tested using binary models of genetic networks, it remains unclear how the method or similar technology will operate with systems of continuous variables. In this study, first, the REVEAL was examined using noisy, continuous data and the results suggested that its application to such data required considerable refinement of the algorithm. Then a new implementation method of REVEAL was proposed. This implementation method was tested through numerical experiments. The results of the simulations demonstrated the potential of the proposed method for extracting gene associations.

关键词： Reverse engineering

来源：评论

学校读者我要写书评

暂无评论

O63: Leveraging global and local genomic data to guide equitable carrier screening: From Genome Aggregation Database (gnomAD) to Qatar Genome

Genetics in Medicine Open

引用

Genetics in Medicine Open 2025年 3卷 102632-102632页

作者： Aarabi, Mahmoud Mbarek, Hamdi Bashar, Aryan Soman, Vishal Al-Mulla, Hajer Nkrumah, Esther Schmitz, Matthew Darabi, Helia Wang, John Kiehl, Paris Sethi, Rahil Saad, Chadi Rajkovic, Aleksandar Yatsenko, Svetlana Chandran, Uma Departments of Pathology and Obstetrics Gynecology and Reproductive Sciences University of Pittsburgh School of Medicine； Medical Genetics and Genomics Laboratories University of Pittsburgh Medical Center (UPMC) Pittsburgh PA Qatar Genome Program Qatar Foundation； Qatar Precision Health Institute Doha Qatar Data Science Graduate Program University of Colorado Boulder Boulder CO Department of Biomedical Informatics University of Pittsburgh School of Medicine Pittsburgh PA Joan H. Marks Graduate Program in Human Genetics Sarah Lawrence College New York NY Temerty Faculty of Medicine University of Toronto Toronto ON Canada Medical Genetics and Genomics Laboratories University of Pittsburgh Medical Center (UPMC) Department of Pediatrics University of Pittsburgh School of Medicine Pittsburgh PA Department of Microbiology Immunology and Pathology Colorado State University Fort Collins CO Department of Pathology and Institute of Human Genetics University of California San Francisco San Francisco CA Department of Pathology Stanford University School of Medicine Stanford CA

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：