Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference)最新文献_第2页

A Machine Learning-based Approach for Collaborative Non-Adherence Detection during Opioid Abuse Surveillance using a Wearable Biosensor. 使用可穿戴生物传感器的阿片类药物滥用监测过程中基于机器学习的协作非依从性检测方法。

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2019-02-01 DOI: 10.5220/0007382503100318

Rohitpal Singh, Brittany Lewis, Brittany Chapman, Stephanie Carreiro, Krishna Venkatasubramanian

{"title":"A Machine Learning-based Approach for Collaborative Non-Adherence Detection during Opioid Abuse Surveillance using a Wearable Biosensor.","authors":"Rohitpal Singh, Brittany Lewis, Brittany Chapman, Stephanie Carreiro, Krishna Venkatasubramanian","doi":"10.5220/0007382503100318","DOIUrl":"https://doi.org/10.5220/0007382503100318","url":null,"abstract":"Wearable biosensors can be used to monitor opioid use, a problem of dire societal consequence given the current opioid epidemic in the US. Such surveillance can prompt interventions that promote behavioral change. The effectiveness of biosensor-based monitoring is threatened by the potential of a patient's collaborative non-adherence (CNA) to the monitoring. We define CNA as the process of giving one's biosensor to someone else when surveillance is ongoing. The principal aim of this paper is to leverage accelerometer and blood volume pulse (BVP) measurements from a wearable biosensor and use machine-learning for the novel problem of CNA detection in opioid surveillance. We use accelerometer and BVP data collected from 11 patients who were brought to a hospital Emergency Department while undergoing naloxone treatment following an opioid overdose. We then used the data collected to build a personalized classifier for individual patients that capture the uniqueness of their blood volume pulse and triaxial accelerometer readings. In order to evaluate our detection approach, we simulate the presence (and absence) of CNA by replacing (or not replacing) snippets of the biosensor readings of one patient with another. Overall, we achieved an average detection accuracy of 90.96% when the collaborator was one of the other 10 patients in our dataset, and 86.78% when the collaborator was from a set of 14 users whose data had never been seen by our classifiers before.","PeriodicalId":72386,"journal":{"name":"Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference)","volume":"5 ","pages":"310-318"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461698/pdf/nihms-1021566.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9636478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Biomedical Engineering Systems and Technologies: 11th International Joint Conference, BIOSTEC 2018, Funchal, Madeira, Portugal, January 19–21, 2018, Revised Selected Papers 生物医学工程系统与技术:第11届国际联合会议，BIOSTEC 2018，丰沙尔，马德拉，葡萄牙，2018年1月19-21日，修订论文选集

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2019-01-01 DOI: 10.1007/978-3-030-29196-9

S. Badia

引用次数: 0

Inferring the Synaptical Weights of Leaky Integrate and Fire Asynchronous Neural Networks: Modelled as Timed Automata 基于时间自动机的漏积分和火异步神经网络突触权的推断

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2019-01-01 DOI: 10.1007/978-3-030-29196-9_9

Elisabetta De Maria, Cinzia Di Giusto

引用次数: 0

A Multiagent-Based Model for Epidemic Disease Monitoring in DR Congo 基于多主体的刚果民主共和国流行病监测模型

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2018-01-19 DOI: 10.1007/978-3-030-29196-9_17

Jean-Claude Tshilenge Mfumu, Annabelle Mercier, M. Occello, C. Verdier

引用次数: 1

Design and Evolution of an Opto-electronic Device for VOCs Detection. VOCs光电检测装置的设计与发展。

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2018-01-01 DOI: 10.5220/0006558100480055

Ana Carolina Pádua, Susana Palma, Jonas Gruber, Hugo Gamboa, Ana Cecília Roque

{"title":"Design and Evolution of an Opto-electronic Device for VOCs Detection.","authors":"Ana Carolina Pádua, Susana Palma, Jonas Gruber, Hugo Gamboa, Ana Cecília Roque","doi":"10.5220/0006558100480055","DOIUrl":"https://doi.org/10.5220/0006558100480055","url":null,"abstract":"Electronic noses (E-noses) are devices capable of detecting and identifying Volatile Organic Compounds (VOCs) in a simple and fast method. In this work, we present the development process of an opto-electronic device based on sensing films that have unique stimuli-responsive properties, altering their optical and electrical properties, when interacting with VOCs. This interaction results in optical and electrical signals that can be collected, and further processed and analysed. Two versions of the device were designed and assembled. E-nose V1 is an optical device, and E-nose V2 is a hybrid opto-electronic device. Both E-noses architectures include a delivery system, a detection chamber, and a transduction system. After the validation of the E-nose V1 prototype, the E-nose V2 was implemented, resulting in an easy-to-handle, miniaturized and stable device. Results from E-nose V2 indicated optical signals reproducibility, and the possibility of coupling the electrical signals to the optical response for VOCs sensing.","PeriodicalId":72386,"journal":{"name":"Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference)","volume":"1 ","pages":"48-55"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6071850/pdf/emss-76350.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36373088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Machine Reading for Extraction of Bacteria and Habitat Taxonomies. 细菌和生境分类提取的机器阅读。

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2015-01-01 Epub Date: 2016-01-05 DOI: 10.1007/978-3-319-27707-3_15

Parisa Kordjamshidi, Wouter Massa, Thomas Provoost, Marie-Francine Moens

{"title":"Machine Reading for Extraction of Bacteria and Habitat Taxonomies.","authors":"Parisa Kordjamshidi, Wouter Massa, Thomas Provoost, Marie-Francine Moens","doi":"10.1007/978-3-319-27707-3_15","DOIUrl":"https://doi.org/10.1007/978-3-319-27707-3_15","url":null,"abstract":"There is a vast amount of scientific literature available from various resources such as the internet. Automating the extraction of knowledge from these resources is very helpful for biologists to easily access this information. This paper presents a system to extract the bacteria and their habitats, as well as the relations between them. We investigate to what extent current techniques are suited for this task and test a variety of models in this regard. We detect entities in a biological text and map the habitats into a given taxonomy. Our model uses a linear chain Conditional Random Field (CRF). For the prediction of relations between the entities, a model based on logistic regression is built. Designing a system upon these techniques, we explore several improvements for both the generation and selection of good candidates. One contribution to this lies in the extended exibility of our ontology mapper that uses an advanced boundary detection and assigns the taxonomy elements to the detected habitats. Furthermore, we discover value in the combination of several distinct candidate generation rules. Using these techniques, we show results that are significantly improving upon the state of art for the BioNLP Bacteria Biotopes task.","PeriodicalId":72386,"journal":{"name":"Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference)","volume":"574 ","pages":"239-255"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4827342/pdf/nihms742657.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34459914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Online Social Networks Flu Trend Tracker: A Novel Sensory Approach to Predict Flu Trends 在线社交网络流感趋势追踪器:一种预测流感趋势的新颖感官方法

Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) Pub Date : 2012-01-01 DOI: 10.1007/978-3-642-38256-7_24

Harshavardhan Achrekar, Avinash Gandhe, Ross Lazarus, Ssu-Hsin Yu, Benyuan Liu

引用次数: 24