检索结果-内蒙古大学图书馆

Annual International conference of the ieee Engineering in Medicine and biology Society (EMBC)

作者： Emmanouil G. Spanakis Ilias Politis Evangelos Markakis Dimitra Papatsaroucha Athanasios Vasileios Grammatopoulos Vaios Bolgouras Anna Angelogianni Christos Xenakis Vangelis Sakkalis Computational Biomedicine Laboratory Institute of Computer Science Foundation for Research and Technology - Hellas Heraklion Crete Greece ISI Athena Research Center Greece Patras Greece InQbit Innovations SRL Romania Electrical & Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Systems Security Lab University of Piraeus Greece

Drifted by the hype of new and efficient machine learning and artificial intelligence models aiming to unlock the information wealth hidden inside heterogeneous datasets across different markets and disciplines, healthcare data are in the center of novel technological advancements in predictive health diagnostics, remote healthcare, assistive leaving and wellbeing. Nevertheless, this emerging market has underlined the necessity of developing new methods and updating existing ones for preserving the privacy of the data and their owners, as well as, ensuring confidentiality and trust throughout the health care data processing pipelines. This paper presents one of the key innovations of a Horizon Europe funded project named "TRUSTEE", which focuses on building a trust and privacy framework for cross-European data exchange by employing a secure and private federated framework to empower companies, organizations, and individuals to securely access data across different disciplines, use and re-use data and metadata to extract knowledge with trust. In particular we present our work on implementing strong authentication and continuous authorization schemes based on the duality of eIDAS trust framework and Self Sovereign Identity (SSI) management to ensure security and trust over authentication, authorization and accounting processes for healthcare.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Probabilistic Framework for Reliability Analysis of Information-Theoretic CAD Systems in Mammography

Probabilistic Framework for Reliability Analysis of Informat...

引用

Annual International conference of the ieee Engineering in Medicine and biology Society (EMBC)

作者： Piotr A. Habas Jacek M. Zurada Adel S. Elmaghraby Georgia D. Tourassi Computational Intelligence Laboratory University of Louisville Louisville KY USA Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Department of Computer Engineering and Computer Science University of Louisville Louisville KY USA Duke Advanced Imaging Laboratories Department of Radiology Duke University Medical Center Durham NC USA

The purpose of this study is to develop and evaluate a probabilistic framework for reliability analysis of information-theoretic computer-assisted detection (IT-CAD) systems in mammography. The study builds upon our previous work on a feature-based reliability analysis technique tailored to traditional CAD systems developed with a supervised learning scheme. The present study proposes a probabilistic framework to facilitate application of the reliability analysis technique for knowledge-based CAD systems that are not feature-based. The study was based on an information-theoretic CAD system developed for detection of masses in screening mammograms from the Digital Database for Screening Mammography (DDSM). The experimental results reveal that the query-specific reliability estimate provided by the proposed probabilistic framework is an accurate predictor of CAD performance for the query case. It can also be successfully applied as a base for stratification of CAD predictions into clinically meaningful reliability groups (i.e., HIGH, MEDIUM, and LOW). Based on a leave-one-out sampling scheme and ROC analysis, the study demonstrated that the diagnostic performance of the IT-CAD is significantly higher for cases with HIGH reliability (Az=0.92plusmn0.03) than for those stratified as MEDIUM (Az=0.84plusmn0.02) or LOW reliability predictions (Az=0.78plusmn0.02)

关键词： Information analysis Mammography Design automation Laboratories Cities and towns USA Councils Supervised learning Application software Spatial databases Delta-sigma modulation

来源：评论

学校读者我要写书评

暂无评论

PepPFN: protein-peptide binding residues prediction via pre-trained module-based Fourier Network

PepPFN: protein-peptide binding residues prediction via pre-...

引用

Artificial intelligence (CAI), ieee conference on

作者： Xue Li Ben Cao Hongzhen Ding Na Kang Tao Song College of Computer Science and Technology China University of Petroleum (East China) Qingdao China Centre for Computational Biology Duke-NUS Medical School Singapore School of Computer Science and Technology Dalian University of Technology Dalian China CFAR A*STAR Singapore The Ninth Department of Health Care Administration The Second Medical Center Chinese PLA General Hospital Beijing China

ISBN: (数字)9798350354096

ISBN: (纸本)9798350354102

Molecular activities in vivo, such as protein-peptide binding residues, contribute to understanding disease mechanisms and discovering targeted drugs, but are often limited by the cost of wet experiments. Therefore, this paper proposes a Pre-trained module-based Fourier Network inspired by Fourier Neural Operators for predicting protein-peptide binding residues (PepPFN). First, the model captures highlatent protein representation and implicit information through Bert and ESM, respectively. Subsequently, the contrastive learning module is used to optimize the representation of binding residues to mitigate the effects of data diversity. Furthermore, the order and frequency information of the residual is obtained by strengthening the model with Fourier network. Comprehensive analysis of multiple tasks and protein visualization results demonstrates that PepPFN outperforms state-of-the-art methods on multiple performance metrics. Datasets and the source code is available at https://***/xueleecs/***.

关键词： Proteins Visualization Biological system modeling Source coding Contrastive learning Feature extraction Data models

来源：评论

学校读者我要写书评

暂无评论

Parallel interacting multiview learning: An application to prediction of protein sub-nuclear location

Parallel interacting multiview learning: An application to p...

引用

ieee EMBS International conference on Information Technology Applications in Biomedicine (ITAB)

作者： Olcay Kursun Huseyin Seker Fikret Gürgen Nizamettin Aydin Oleg V. Favorov C. Okan Sakar Department of Computer Engineering Istanbul University 34320 Turkey Department of Computer Engineering Istanbul University Istanbul Turkey Istanbul Universitesi Fatih Istanbul TR Bio-Health Informatics Research Group Centre for Computational Intelligence Department of Informatics Technology De Montfort University Leicester UK Department of Computer Engineering Boğaziçi University Istanbul Turkey Department of Computer Engineering Yildiz Technical University Istanbul Turkey Department of Biomedical Engineering North Carolina State University Chapel Hill NC USA

In some machine learning problems, the dataset has multiple views which may be obtained using different sensors or applying different sampling techniques. These views may have sufficient or partial information about the target concept. In this paper, a method that we called parallel interacting multiview learning (PIML) is proposed in which the views interact during the training process using the predictions of each other together with their original features. This way, the views are expected to strengthen the prediction accuracies of the other views feeding their predictions to the others even during the training process. This technique avoids the way of simply merging features of all views and reaches higher accuracy than its counterparts that do not interact during learning but only combine their predictions after the learning process. PIML is demonstrated on a real bioinformatics dataset for predicting protein sub-nuclear locations.

关键词： Machine learning Merging bioinformatics Informatics Sampling methods Accuracy Pattern recognition Production Protein sequence Speckle

来源：评论

学校读者我要写书评

暂无评论

Augmented cell-graphs for automated cancer diagnosis

引用

bioinformatics 2005年第Sup2期21卷 7-12页

作者： Demir, C Gultekin, SH Yener, B Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA CUNY Mt Sinai Sch Med Dept Pathol New York NY 10029 USA

This work reports a novel computational method based on augmented cell-graphs (ACG), which are constructed from low-magnification tissue images for the mathematical diagnosis of brain cancer (malignant glioma). An ACG is a simple, undirected, weighted and complete graph in which a node represents a cell cluster and an edge between a pair of nodes defines a binary relationship between them. Both the nodes and the edges of an ACG are assigned weights to capture more information about the topology of the tissue. In this work, the experiments are conducted on a dataset that is comprised of 646 human brain biopsy samples from 60 different patients. It is shown that the ACG approach yields sensitivity of 97.53% and specificities of 93.33 and 98.15% (for the inflamed and healthy, respectively) at the tissue level in glioma diagnosis.

关键词： Algorithms Artificial intelligence Brain Neoplasms/pathology Glioma/pathology Humans Image Interpretation, Computer-Assisted/methods Pattern Recognition, Automated/methods Reproducibility of Results Sensitivity and Specificity

来源：评论

学校读者我要写书评

暂无评论

On the Design of A Malleable Chip:A Biologically Motivated Evolvable Hardware

On the Design of A Malleable Chip:A Biologically Motivated E...

引用

2005 International conference on Neural Networks and Brain(ICNN&B’05)

作者： Jong-Chen Chen Yo-Hsien Lin Department of Management Information Systems National YunLin University of Science and Technology

＜正＞Computer hardware has high processing speed;however,it is lack of flexibility in dealing with most real world problems[1].Evolvable neuromolecular hardware,motivated from some biological evidence,which integrates inter- and intra-neuronal information processing,is proposed. Evolvability,self-organizing dynamics,and a close structure-function relationship are three biological features captured in this *** QuartusⅡsystem,a tool developed by the Altera *** simulating digital circuits,is used to test this hardware and perform a series of experiments. The hardware is applied to pattern recognition problem *** result shows that the structures and functions of this hardware are closely related that its outputs change accordingly when we gradually modify the structure, implying this hardware embracing an adaptive fitness landscape that facilitates evolutionary learning.

关键词： Hardware Circuit testing biology computing Information processing Biological system modeling Circuit simulation Digital circuits System testing Performance evaluation Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

TCM-FTP: Fine-Tuning Large Language Models for Herbal Prescription Prediction

TCM-FTP: Fine-Tuning Large Language Models for Herbal Prescr...

引用

ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Xingzhi Zhou Xin Dong Chunhao Li Yuning Bai Yulong Xu Ka Chun Cheung Simon Se Xinpeng Song Runshun Zhang Xuezhong Zho Nevin L. Zhang Department of Computer Science and Technology The Hong Kong University of Science and Technology Hong Kong China Department of Artificial Intelligence Beijing Key Lab of Traffic Data Analysis and Mining School of Computer Science & Technology Institute of Medical Intelligence Beijing Jiaotong University Beijing China Guang’anmen Hospital China Academy of Chinese Medical Sciences Beijing China School of Information Technology Henan University of Chinese Medicine China NVAITC NVIDIA Hong Kong China NVAITC NVIDIA Singapore

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Traditional Chinese medicine (TCM) has relied on specific combinations of herbs in prescriptions to treat various symptoms and signs for thousands of years. Predicting TCM prescriptions poses a fascinating technical challenge with significant practical implications. However, this task faces limitations due to the scarcity of high-quality clinical datasets and the complex relationship between symptoms and herbs. To address these issues, we introduce DigestDS, a novel dataset comprising practical medical records from experienced experts in digestive system diseases. We also propose a method, TCM-FTP (TCM Fine-Tuning Pre-trained), to leverage pre-trained large language models (LLMs) via supervised fine-tuning on DigestDS. Additionally, we enhance computational efficiency using a low-rank adaptation technique. Moreover, TCM-FTP incorporates data augmentation by permuting herbs within prescriptions, exploiting their order-agnostic nature. Impressively, TCM-FTP achieves an F1-score of 0.8031, significantly outperforming previous methods. Furthermore, it demonstrates remarkable accuracy in dosage prediction, achieving a normalized mean square error of 0.0604. In contrast, LLMs without fine-tuning exhibit poor performance. Although LLMs have demonstrated wide-ranging capabilities, our work underscores the necessity of fine-tuning for TCM prescription prediction and presents an effective way to accomplish this.

关键词： Analytical models Accuracy Biological system modeling Large language models Digestive system Mean square error methods Predictive models Data augmentation Faces Diseases

来源：评论

学校读者我要写书评

暂无评论

Insect navigation and communication in flight and migration: A potential model for joining and collision avoidance in MAVs and mobile robots fleet control

Insect navigation and communication in flight and migration:...

引用

ieee conference on Aerospace

作者： Zhanshan Ma Axel W. Krings Richard Millar Feng Wang Jun Chao Computational Biology & Bioinformatics Lab KIZ Chinese Academy of Sciences PRC & Computer Science Department & iBE University of Idaho USA Computer Science Department University of Idaho Moscow ID USA Department of Systems Engineering Naval Postgraduate School MD USA Computer Science Department Kunming University of Science and Technology Kunming China Kunming Institute of Zoology KIZ Chinese Academy and Sciences Kunming China

The human being should be awarded the championship of navigation on the planet, on the virtues that they not only have invented and manufactured the compass, GPS, aircraft, vessel, spacecraft, but also have demonstrated exceptional non-instrumental navigation skills. The Austronesian expansion from the Asian mainland into the Pacific performed by the Pacific navigators, who eventually populated the most remote islands of the Pacific about 4000 years ago, is a vivid example (Wehner 1998). However, animals, especially flying birds and insects are strong contenders. Monarch butterflies can migrate up to 2000 miles from their reproductive sites in the eastern US and Canada to their over-wintering sites in the forests of Mexico, and it is postulated that they may possess a biological equivalent of a low-resolution GPS system that is based on the magnetic field of the earth. In fact, even the long-legged ants (Cataglyphis fortis) in the Saharan desert use the dead-reckoning navigation strategy, which is attributed to the Polynesians, but the ants apparently have acquired the capability much earlier, given the relative short evolutionary history of humans. In this article, we briefly review the state-of-the-art research on insect navigation and communication used in flight and communication, with the objective to inspire cross-disciplinary studies in aerospace engineering, biology and computer science. After a brief review, we overview and identify seven cross-disciplinary research topics that may draw on inspirations from insect navigation and communication in flight and migration. These topics include: ants colony inspired swarm intelligence, honeybee inspired group decision-making, insect sociobiology, MAV/mobile robot flight control and remote control of insect flights, optimal migration strategy, Quorum sensing, and joining and collision avoidance for MAV fleet control. An interesting question one may pose is: given the rich and advanced navigation and communication t

关键词： Insects Navigation Visualization Birds Sun

来源：评论

学校读者我要写书评

暂无评论

A Cloud-unaware Programming Model for Easy Development of Composite Services

A Cloud-unaware Programming Model for Easy Development of Co...

引用

ieee International conference on Cloud Computing Technology and Science (CloudCom)

作者： Enric Tejedor Jorge Ejarque Francesc Lordan Roger Rafanell Javier Alvarez Daniele Lezzi Raul Sirvent Rosa M. Badia Universitat Poliltècnica de Catalunya Barcelona Spain Barcelona Supercomputing Center Barcelona Spain Artificial Intelligence Research Institute (IIIA) Spanish National Research Council Spain

Cloud computing is inherently service-oriented: cloud applications are delivered to consumers as services via the Internet. Therefore, these applications can potentially benefit from the Service-Oriented Architecture (SOA) principles: they can be programmed as added-value services composed by pre-existing ones, thus favouring code reuse. However, new programming models are required to simplify their development, along with systems that are capable of orchestrating the execution of the resulting SaaS in the Cloud. In that regard, this paper presents Service Super scalar (Servicess), an alternative to existing PaaS which provides a programming model and execution runtime to ease the development and execution of service-based applications in clouds. Servicess is a task-based model: the user is only required to select the tasks, which can be services or regular methods, to be spawned asynchronously. The application, a composite service, is programmed in a totally sequential way and no API call must be included in the code. The runtime is in charge of automatically orchestrating the execution of the tasks in the Cloud, as well as of elastically deploying new virtual resources depending on the load. After describing the main characteristics of the programming model and the runtime, we evaluate the productivity of Servicess and show how it offers a good trade-off between programmability and runtime performance.

关键词： Runtime Programming Java Cloud computing computational modeling bioinformatics Service oriented architecture

来源：评论

学校读者我要写书评

暂无评论

Probing glioblastoma and its microenvironment using single-nucleus and single-cell sequencing

Probing glioblastoma and its microenvironment using single-n...

引用

ieee International conference on bioinformatics and Biomedicine

作者： Sen Peng Sanhita Rath Connor Vuong Saumya Bollam Jenny Eschbacher Xishuang Dong Shwetal Mehta Nader Sanai Michael Berens Seungchan Kim Harshil Dhruv Cancer and Cell Biology Division The Translational Genomics Research Institute Division of Neurobiology Barrow Brain Tumor Research Center Barrow Neurological Institute St. Joseph's Hospital and Medical Center Center for Computational Systems Biology and Electrical and Computer Engineering Roy G. Perry College of Engineering Prairie View A&M University

ISBN: (纸本)9781728118680

Single-cell (scSeq) and single-nucleus sequencing (snSeq) are powerful tools to investigate cancer genomics at single cell resolution. Multiple studies have recently illuminated intratumoral heterogeneity in glioblastoma, however, the majority focused on molecular complexity of tumor cells, without considering unexplored host cell types that contribute to the microenvironment around tumor. To address the glioblastoma microenvironment composition and potential tumor-host interactions, we performed deep coverage sequencing of freshly resected primary GBM patient tissue without implementing any tumor enrichment strategies. The sequencing resulted in 902 cells and 1186 nuclei, respectively, passing quality control and with low mitochondrial gene percentage. We customized reference transcriptome by listing gene transcript loci as exons to take into account immature RNA, which greatly improved the alignment rate for single-nucleus data. We applied Cell Ranger pipelines (Version 3.0.2) and Seurat package (Version 2.3.1) and discovered 10 clusters in both scSeq and snSeq. Pathway analysis of each cluster signature in scSeq data along with known GBM microenvironment cell signatures revealed glioma tumor population along with surrounding microglia/macrophages, astrocytes, pericytes, oligodendrocytes, T cells and endothelial cells. The analysis of snSeq was able to capture the majority of cell types from patient tissues (tumor and microenvironment cells), but interestingly presented different cell type composition in microenvironment cell types such as microglia/macrophages. Integrating single-cell and single-nucleus transcriptomic data using canonical correlation analysis facilitated a comparison of snSeq and scSeq, contrasting depiction for certain cell types (e.g. NKX6-2 gene in Oligodendrocytes). Differential analysis of pathways between tumor and microenvironment cells unveiled potentially rewired pathways such as double strand break repair pathway. Our results demonstrat

关键词： glioblastoma microenvironment single cell sequencing single nucleus sequencing Microenvironments cell type Lipoblastoma SINGLE CELL Cell Microenvironment Tumours Analyses, Sequence

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：