检索结果-内蒙古大学图书馆

Existing predictive Models for Postoperative Pulmonary Complications Perform Poorly in a Head and Neck Surgery Population

引用

JOURNAL OF MEDICAL SYSTEMS 2019年第10期43卷 312-312页

作者： Wood, C. Burton Shinn, Justin R. Rees, Andrew B. Patel, Priyesh N. Freundlich, Robert E. Smith, Derek K. McEvoy, Matthew D. Rohde, Sarah L. Vanderbilt Univ Med Ctr Dept Otolaryngol Head & Neck Surg 1215 21st Ave South Nashville TN 37235 USA Vanderbilt Univ Sch Med Nashville TN 37212 USA Vanderbilt Univ Med Ctr Dept Anesthesiol 1215 21st Ave South Nashville TN USA Vanderbilt Univ Med Ctr Dept Biomed Informat 1215 21st Ave South Nashville TN USA Vanderbilt Univ Med Ctr Dept Oral & Maxillofacial Surg 1215 21st Ave South Nashville TN USA

Postoperative pulmonary complications (PPCs) are common following major surgical procedures. Risk stratification tools have been developed to identify patients at risk for PPCs. While otolaryngology cases were included in the development of common predictive tools, they comprised small percentages in each tool. It is unclear how these tools perform in patients undergoing major head and neck surgery with free flap reconstruction. This retrospective review studied all free flap reconstructions in head and neck surgery over a 12-year period at a single institution in the southeastern US. Baseline demographic and medical information were included for each case. All cases were reviewed for development of major PPCs, including pneumonia and respiratory failure. The cohort underwent risk stratification using the ARISCAT and Gupta pulmonary risk indices. Performance of these predictive models for head and neck surgery was determined through receiver-operator curve comparison. 794 patients were identified with a median age of 62 years (IQR 41-83). Sixty-five percent were male. Forty-three (5.4%) developed pneumonia, 23 patients developed respiratory failure (2.9%), and 38 patients developed both (4.8%), resulting in a total PPC proportion of 13.1% (n = 104). Both ARISCAT and Gupta pulmonary risk indices demonstrated low discrimination to predict PPCs in head and neck free flap reconstruction, with areas under the curve of 0.60 and 0.65, respectively. Two major indices for prediction of postoperative pulmonary complications do not accurately identify risk in patients undergoing major head and neck surgery. Further studies are needed to develop predictive tools for PPCs in this high-risk population.

关键词： Microvascular free flap reconstruction Post-operative complications Risk stratification predictive algorithms

来源：评论

学校读者我要写书评

暂无评论

Employee Attrition Analysis Using predictive Techniques 2nd

Employee Attrition Analysis Using Predictive Techniques

引用

2nd International Conference on Information and Communication Technology for Intelligent Systems (ICTIS)

作者： Srivastava, Devesh Kumar Nair, Priyanka Manipal Univ Jaipur Dept CSE & IT Jaipur Rajasthan India

ISBN: (纸本)9783319636733;9783319636726

Employee churn is an unsolicited aftermath of our blooming economy. Attrition may be defined as voluntary or involuntary resignation of a serving employee from an organization. Employee churn can incur a colossal cost to the firm. However, furtherance to prediction and control over attrition can give quality results. Earmarking the risk of attrition, the management can take required steps to retain the high valued talent. Workforce Analytics can be applied to reduce the overall business risk by predicting the employee churn. predictive Analytics is the field of study that employs statistical analysis, data mining techniques and machine learning to predict the future events with accuracy based on past and current situation. The paper presents a framework for predicting the employee attrition with respect to voluntary termination employing predictive analytics.

关键词： Turnover prediction predictive analytics Data mining Employee attrition predictive algorithms

来源：评论

学校读者我要写书评

暂无评论

Unraveling the space grammar of terrorist attacks: A TWC approach

引用

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 2018年 132卷 230-254页

作者： Buscema, Massimo Sacco, Pier Luigi Massini, Giulia Della Torre, Francesca Brogi, Marco Salonia, Massimo Ferilli, Guido Semeion Res Ctr Via Sersale 117 I-00128 Rome Italy Univ Colorado Dept Math & Stat Sci Denver CO 80202 USA IULM Univ Via Carlo Bo 1 I-20143 Milan Italy Harvard Univ MetaLAB Harvard Cambridge MA 02138 USA PWC PricewaterhouseCoopers SPA Human Capital Rome Italy LUISS Libera Univ Int Sociali Guido Carli Int Rel Rome Italy

In this paper, we introduce a new approach to the analysis and prediction of the spatial pattern of terrorist attacks. Our analysis makes use of a new methodology that is based upon a topological rather than geometric approach. It exploits the space grammar of the observed events to derive complex inferences which relate to the deep structural layers of the data generating process, and to the organizational architecture of its spatial distribution. We test our methodology on two of the currently most important and virulent theaters of terrorist activity, Libya and Syria, and we find that our methodology provides a rich array of insights which cannot be expected to be generated by more traditional geographical profiling methods.

关键词： Terrorist attacks Topological Weighted Centroid (TWC) Geographic profiling Probabilistic map predictive algorithms Clustering

来源：评论

学校读者我要写书评

暂无评论

Automated Quantification of Hydroxyl Reactivities: Prediction of Glycosylation Reactions

引用

Angewandte Chemie 2021年第22期133卷

作者： Chun-Wei Chang Mei-Huei Lin Chieh-Kai Chan Kuan-Yu Su Chia-Hui Wu Wei-Chih Lo Sarah Lam Yu-Ting Cheng Pin-Hsuan Liao Chi-Huey Wong Cheng-Chung Wang Institute of Chemistry Academia Sinica Taipei 115 Taiwan The Genomics Research Center Academia Sinica Taipei 115 Taiwan Department of Chemistry The Scripps Research Institute 10550 N Torrey Pines Road La Jolla 92037 USA Chemical Biology and Molecular Biophysics Program Taiwan International Graduate Program (TIGP) Academia Sinica Taipei 115 Taiwan

The stereoselectivity and yield in glycosylation reactions are paramount but unpredictable. We have developed a database of acceptor nucleophilic constants (Aka) to quantify the nucleophilicity of hydroxyl groups in glycosylation influenced by the steric, electronic and structural effects, providing a connection between experiments and computer algorithms. The subtle reactivity differences among the hydroxyl groups on various carbohydrate molecules can be defined by Aka, which is easily accessible by a simple and convenient automation system to assure high reproducibility and accuracy. A diverse range of glycosylation donors and acceptors with well-defined reactivity and promoters were organized and processed by the designed software program “GlycoComputer” for prediction of glycosylation reactions without involving sophisticated computational processing. The importance of Aka was further verified by random forest algorithm, and the applicability was tested by the synthesis of a Lewis A skeleton to show that the stereoselectivity and yield can be accurately estimated.

关键词： carbohydrates diastereoselectivity hydroxyl glycosylation predictive algorithms

来源：评论

学校读者我要写书评

暂无评论

Predicting Posttraumatic Stress Disorder Risk: A Machine Learning Approach

引用

JMIR MENTAL HEALTH 2019年第7期6卷 e13946页

作者： Wshah, Safwan Skalka, Christian Price, Matthew Univ Vermont 33 Colchester Ave Burlington VT 05405 USA

Background: A majority of adults in the United States are exposed to a potentially traumatic event but only a handful go on to develop impairing mental health conditions such as posttraumatic stress disorder (PTSD). Objective: Identifying those at elevated risk shortly after trauma exposure is a clinical challenge. The aim of this study was to develop computational methods to more effectively identify at-risk patients and, thereby, support better early interventions. Methods: We proposed machine learning (ML) induction of models to automatically predict elevated PTSD symptoms in patients 1 month after a trauma, using self-reported symptoms from data collected via smartphones. Results: We show that an ensemble model accurately predicts elevated PTSD symptoms, with an area under the curve (AUC) of .85, using a bag of support vector machines, naive Bayes, logistic regression, and random forest algorithms. Furthermore, we show that only 7 self-reported items (features) are needed to obtain this AUC. Most importantly, we show that accurate predictions can be made 10 to 20 days posttrauma. Conclusions: These results suggest that simple smartphone-based patient surveys, coupled with automated analysis using ML-trained models, can identify those at risk for developing elevated PTSD symptoms and thus target them for early intervention.

关键词： PTSD machine learning predictive algorithms

来源：评论

学校读者我要写书评

暂无评论

A First Course in predictive Control, Second Edition [Bookshelf]

引用

IEEE Control Systems 2019年第4期39卷 80-80页

作者： Clara M. Ionescu Electrical Energy Metals Mechanical Constructions and Systems Ghent University Belgium

As the demand for individualized products increases, there is a need for advanced control at the supervisory level, where model predictive control (MPC) becomes an established solution in industry. This is an excellent text that provides numerous MPC algorithms supported by highly relevant, illustrative industry examples. The book opens with a comprehensive chapter about industry’s need for predictive control, reminding readers that MPC originated in business and expanded into academia, where it captured the attention of several seminal researchers. Addresses some of the following topics: major concepts of PID; properties of model-based control and requirements of MPCs; predictive function control (PFC); basic predictive control algorithms; principle components of dual-mode MPC; and constraint handling mechanisms. The book has a set of Matlab code (from MathWorks) and sources to help readers reproduce the illustrations in each chapter. A First Course in predictive Control can be considered as a textbook, since it includes introductory subchapters to guide lecturers and help filter the sections for teaching from areas outside the course. In summary, this book provides an excellent course in MPC, presented in the form of a textbook, and great support for lecturers. It also offers a substantial starting point for MPC-related research for industrial applications.

关键词： Book reviews predictive control predictive algorithms Modeling

来源：评论

学校读者我要写书评

暂无评论

Validating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a Prospective Cohort Study

引用

JMIR RESEARCH PROTOCOLS 2018年第9期7卷 e176页

作者： Kakarmath, Sujay Golas, Sara Felsted, Jennifer Kvedar, Joseph Jethwani, Kamal Agboola, Stephen Partners HealthCare Partners Connected Hlth Data Sci & Analyt Unit 25 New Chardon StSuite 300 Boston MA 02114 USA Massachusetts Gen Hosp Dept Dermatol Boston MA 02114 USA Harvard Med Sch Dept Dermatol Boston MA USA Partners HealthCare Partners Connected Hlth Boston MA 02114 USA

Background: Big data solutions, particularly machine learning predictive algorithms, have demonstrated the ability to unlock value from data in real time in many settings outside of health care. Rapid growth in electronic medical record adoption and the shift from a volume based to a value-based reimbursement structure in the US health care system has spurred investments in machine learning solutions. Machine learning methods can be used to build flexible, customized, and automated predictive models to optimize resource allocation and improve the efficiency and quality of health care. However, these models are prone to the problems of overfitting, confounding, and decay in predictive performance over time. It is, therefore, necessary to evaluate machine learning-based predictive models in an independent dataset before they can be adopted in the clinical practice. In this paper, we describe the protocol for independent, prospective validation of a machine learning-based model trained to predict the risk of 30-day re-admission in patients with heart failure. Objective: This study aims to prospectively validate a machine learning-based predictive model for inpatient admissions in patients with heart failure by comparing its predictions of risk for 30-day re-admissions against outcomes observed prospectively in an independent patient cohort. Methods: All adult patients with heart failure who are discharged alive from an inpatient admission will be prospectively monitored for 30-day re-admissions through reports generated by the electronic medical record system. Of these, patients who are part of the training dataset will be excluded to avoid information leakage to the algorithm. An expected sample size of 1228 index admissions will be required to observe a minimum of 100 30-day re-admission events. Deidentified structured and unstructured data will be fed to the algorithm, and its prediction will be recorded. The overall model performance will be assessed using the conc

关键词： electronic medical records heart failure machine learning predictive algorithms readmissions

来源：评论

学校读者我要写书评

暂无评论

A precision medicine approach to a patient with unresolved pain following orthopedic surgery: A case report

引用

Journal of Medical Case Reports 2017年第1期11卷 1-3页

作者： Gazzaniga, David Brenton, Ashley Meshkin, Brian Newport Orthopedic Institute Newport Beach CA United States Proove Biosciences 15326 Alton Pkwy Irvine 92618 CA United States

Background: Precision medicine is a promising technology in patient care that combines genetic analysis with clinical data, such as health, behavioral, functional, environment, and lifestyle information. Here we present the case of a 54-year old woman who, following an accident, had uncontrolled chronic pain and was subsequently labeled a drug seeker. Case presentation: A 54-year-old white woman who was experiencing severe calf pain was referred for treatment. Her pain was insufficiently controlled immediately following knee arthroplasty with multiple opioid medications, as well as non-opioids. Precision medicine testing was ordered for her so that we could assess her pain sensitivity objectively to determine if the pill seeker designation was correct and to determine the best medications for her. Based on the Proove profiles, we determined that she had moderately low pain sensitivity, which means that clinically she may underreport pain and may have decreased medication needs. This result suggested that her continued reporting of unresolved pain was probably due to a condition unresolved by her right knee arthroplasty. In addition, she was found to be at low risk of opioid addiction, based on the Proove Opioid Risk Profile. Taken together, along with the high levels of pain she described, we determined that her pain was not properly controlled and that the designation of pill seeker was incorrect. The next step was to determine which medications and which doses would result in the most favorable outcomes for our patient. To determine this, we used the results of the Proove Opioid Response, Proove Drug Metabolism, and Proove Non-Opioid Profiles to guide her treatment. We reduced her pain medications to a single opioid, Vicodin (acetaminophen and hydrocodone), which also eliminated the adverse side effects she experienced. Conclusions: Precision medicine offers an important health care decision tool which can reduce emotional and physical costs to patients and may re

关键词： Opioid risk Orthopedics Pain management Precision medicine predictive algorithms

来源：评论

学校读者我要写书评

暂无评论

An optimal centralized predictive control scheme applied to a Non-Square MIMO benchmark problem

引用

IFAC-PapersOnLine 2016年第13期49卷 59-64页

作者： Abraham, Anuj Pappa, N. Department of Instrumentation Engineering Madras Institute of Technology Anna University Chennai600044 India

This paper aims at the implementation of advanced control technique such as Generalized predictive Control (GPC) for non-square Multi-Input-Multi-Output (MIMO) benchmark problem. The process considered is a coupled distillation column (3 input, 2 output) studied by Levein and Morari. The design approach for tuning controller parameters in conventional methods of a non-square system is a big challenge, as it involves computational complexities. In this work, predictive algorithm with constraints on the input and output control signals are developed and compared with the PID controller by retaining its non-minimum phase characteristics. GPC uses Controlled Autoregressive and Integrated Moving-Average (CARIMA) model. Simulation studies demonstrate the superiority of the constrained GPC over GA-PID controller for a non-square multivariable process. The effectiveness of the advance control structure ensures the reduction in computational complexities and fast convergences with better tracking capabilities. © 2016

关键词： Controllers Benchmarking Communication channels (information theory) Computational complexity Distillation columns Electric control equipment MIMO systems predictive control systems Proportional control systems Three term control systems Conventional methods Generalized predictive control Multi input multi output Multi variables Multivariable process Non square systems predictive algorithms predictive control

来源：评论

学校读者我要写书评

暂无评论

Accuracy Comparison of predictive algorithms of Data Mining: Application in Education Sector

引用

International Conference on Advances in Computing, Communication and Control (ICAC3)

作者： Sharma, Mamta Mavani, Monali SIES Coll Management Studies Fac MCA Navi Mumbai Maharashtra India

ISBN: (纸本)9783642184390

Prediction is growing area of research which is attracting many researchers. Prediction is applied to almost all the sectors. Much commercial Business Intelligence software is available in which prediction is one of the features. With the advent of Open Source Technologies, it has become possible for education sector which normally has low IT budget, to take maximum advantage of Information and Communication Technologies(ICT). This paper describes the use of Open source Software Knime for prediction of students result based upon various independent(predictor) variables and value of dependent variable can be predicted using decision tree, SOTA (Self Organizing Tree Algorithm) and Naive Bayes This paper compares these three predictive algorithms present in Knime in terms of accuracy. Predicted results are compared with the actual result in order to measure accuracy and recommends best predictive algorithm for forecasting. This paper also demonstrates the use of Moodie - Open Source Learning Management System (LMS) Logs as one of the attributes in predicting the student results.

关键词： predictive algorithms Decision tree SOTA (Self Organizing Tree Algorithm) Naive Bayes Knime Moodle

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：