scholarly journals Neural Query System: Data-Mining From Within the NEURON Simulator

2006 ◽  
Vol 4 (2) ◽  
pp. 163-176 ◽  
Author(s):  
William W. Lytton
Keyword(s):  
Data Mining ◽  
System Data ◽  
Query System ◽  
Neuron Simulator

scholarly journals Systematic Methods on Machine Learning Techniques for Clinical Predictive Modelling

2020 ◽  
Vol 9 (5) ◽  
pp. 288-297
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
High Performance ◽  
Predictive Modelling ◽  
Medical Application ◽  
Medical Data ◽  
Machine Learning Techniques ◽  
Screening Process ◽  
Huge Data ◽  
System Data

Predictive modelling is a mathematical technique which uses Statistics for prediction, due to the rapid growth of data over the cloud system, data mining plays a significant role. Here, the term data mining is a way of extracting knowledge from huge data sources where it’s increasing the attention in the field of medical application. Specifically, to analyse and extract the knowledge from both known and unknown patterns for effective medical diagnosis, treatment, management, prognosis, monitoring and screening process. But the historical medical data might include noisy, missing, inconsistent, imbalanced and high dimensional data.. This kind of data inconvenience lead to severe bias in predictive modelling and decreased the data mining approach performances. The various pre-processing and machine learning methods and models such as Supervised Learning, Unsupervised Learning and Reinforcement Learning in recent literature has been proposed. Hence the present research focuses on review and analyses the various model, algorithm and machine learning technique for clinical predictive modelling to obtain high performance results from numerous medical data which relates to the patients of multiple diseases.

Using Data Mining to Predict Safety Actions from FDA Adverse Event Reporting System Data

2007 ◽  
Vol 41 (5) ◽  
pp. 633-643 ◽  
Author(s):  
Alan M. Hochberg ◽  
Stephanie J. Reisinger ◽  
Ronald K. Pearson ◽  
Donald J. O’Hara ◽  
Kevin Hall
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
System Data ◽  
Using Data

Data Mining and Explorative Multivariate Data Analysis for Customer Satisfaction Study

2011 ◽  
pp. 243-266 ◽  
Author(s):  
Rosaria Lombardo
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Customer Satisfaction ◽  
Management System ◽  
Multivariate Data Analysis ◽  
Learning Management System ◽  
Multivariate Data ◽  
Data Sets ◽  
System Data ◽  
Learning Management

By the early 1990s, the term “data mining” had come to mean the process of finding information in large data sets. In the framework of the Total Quality Management, earlier studies have suggested that enterprises could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk customers/consumers and allow for more timely interventions (Macfadyen & Dawson, 2009). The Learning Management System data and the subsequent Customer Interaction System data can help to provide “early warning system data” for risk detection in enterprises. This chapter confirms and extends this proposition by providing data from an international research project investigating on customer satisfaction in services to persons of public utility, like education, training services and health care services, by means of explorative multivariate data analysis tools as Ordered Multiple Correspondence Analysis, Boosting regression, Partial Least Squares regression and its generalizations.

scholarly journals Reexamining Content-Enriched Access: Its Effect on Usage and Discovery

2011 ◽  
Vol 72 (5) ◽  
pp. 412-427 ◽  
Author(s):  
Yuji Tosaka ◽  
Cathy Weng
Keyword(s):  
Data Mining ◽  
Keyword Search ◽  
Academic Library ◽  
Library System ◽  
Bibliographic Records ◽  
Library Users ◽  
System Data ◽  
Search Option

Content-enriched metadata in bibliographic records is considered helpful to library users in identifying and selecting library materials for their needs. The paper presents a study, using circulation data from a medium-sized academic library, of the effect of content-enriched records on library materials usage. The study also examines OPAC search transactions of circulated items to learn how enriched metadata is used. The findings show that enhanced records were overall associated with higher circulation rates and that keyword search was the most frequently used search option directly associated with circulation. Contents data can play a key role in discovery. Libraries should continue to provide and exploit content-enriched metadata. The combination of optimal library system data mining capability, postsearching evaluation, and OPAC display are crucial to achieve content-enriched access.

Evaluating the Effective Factors of Hospital Rooms on Patients’ Recovery Using the Data Mining Method

2021 ◽  
pp. 193758672110313
Author(s):  
S. Nikabadi ◽  
H. Zabihi ◽  
A. Shahcheraghi
Keyword(s):  
Data Mining ◽  
Length Of Hospital Stay ◽  
Knowledge Discovery In Databases ◽  
Hospital Environments ◽  
Pearson Coefficient ◽  
System Data ◽  
Python Programming ◽  
Nursing Station ◽  
The Relationship ◽  
Interior Environment

Objectives: This study aims to investigate the effective environmental factors of hospital rooms in patients’ recovery through data mining techniques. Background: Previous studies have shown the positive effect of the interior environment of the hospitals on patients’ recovery. The methods of these studies were mainly based on the evidence and patients’ perception while hospital environments are associated with a large amount of data that make them an appropriate case for data mining studies. But data mining studies in hospitals mainly focused on medical and management purposes rather than evaluating the interior environment condition. Methods: We analyzed the hospital information system data of a hospital using Python programming language and some of its libraries. Preprocessing and eliminating the outliers, labeling and clustering of diseases, data visualization and analysis, final evaluation, and concluding were done using the knowledge discovery in databases process. Results: Pearson coefficient value for rooms’ area was .5 and, respectively, for the distance from the ward entrance and nursing station were .75 and .70. The χ2 values for the variables of room types, location, and occupation were 24.62, 18.98, and 21.53, respectively, and for the beds’ location was 0.12. Conclusions: The results confirmed the correlation of the length of stay with the room types, location, and occupation, distance from the nursing station and ward entrance and also showed a moderate correlation with the rooms’ area. However, no evidence was found about the relationship between the beds’ location in rooms and patients’ length of hospital stay.

scholarly journals Membangun Framework Repository Source Code Algoritma Komputer pada Platform Web

JURNAL TIKA ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 105-109
Author(s):  
Amrullah Amrullah ◽  
Mutasar Mutasar
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Image Processing ◽  
Expert System ◽  
Computer System ◽  
Source Code ◽  
Decision System ◽  
Information Searching ◽  
System Data ◽  
System Information

Era Revolusi Industri 4.0 programmer dihadirkan platform CMS, Web builder yang mempercepat pembuatan program seperti create templete responsive/dinamis, CRUD dan grafik namun belum adanya framework untuk membangun source code pada platform web yang memecahkan alur proses pada sebuah algoritma sehingga akan membantu programmer/peneliti dalam menyelesaikan masalah aritmatika/logical proses pada sebuah algoritma/metode jika di-implementasikan kedalam source code platform web HTML, PHP, CSS. Urgensi permasalahan ini harus adanya sistem repository yang menyediakan source code algoritma komputer meliputi (expert system, data mining, decision system, artificial intelligence, kriptografi/security computer, system information, searching, image processing). Adanya repository ini akan memberikan kemudahan dalam menghasilkan source code algoritma/metode komputer untuk dapat digunakan sebagai, modify,combine, comparation, example, trying, testing , implementation, sehingga akan mudah dalam penyelesaian program penelitian dan membantu mempercepat laju skill programmer/peneliti di perguruan tinggi.

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