scholarly journals Revealing Associations between Diagnosis Patterns and Acupoint Prescriptions Using Medical Data Extracted from Case Reports

2019 ◽  
Vol 8 (10) ◽  
pp. 1663 ◽  
Author(s):  
Cheol-Han Kim ◽  
Da-Eun Yoon ◽  
Ye-Seul Lee ◽  
Won-Mo Jung ◽  
Joo-Hee Kim ◽  
...  
Keyword(s):  
Network Analysis ◽  
Case Reports ◽  
Medical Data ◽  
Medical Doctors ◽  
Inverse Document Frequency ◽  
Qualitative And Quantitative ◽  
Bladder Disease ◽  
Document Frequency ◽  
The Relationship ◽  
Disease Specific

Objective: The optimal acupoints for a particular disease can be determined by analysis of diagnosis patterns. The objective of this study was to reveal the association between such patterns and the acupoints prescribed in clinical practice using medical data extracted from case reports. Methods: This study evaluated online virtual diagnoses made by currently practicing Korean medical doctors (N = 80). The doctors were presented with 10 case reports published in Korean medical journals and were asked to diagnose the patients and prescribe acupoints accordingly. A network analysis and the term frequency-inverse document frequency (tf-idf) method were used to analyse and quantify the relationship between diagnosis patterns and prescribed acupoints. Results: The network analysis showed that ST36, LI4, LR3, and SP6 were the most frequently used acupoints across all diagnoses. The tf-idf values showed the acupoints used for specific diseases, such as BL40 for bladder disease and LU9 for lung disease. Conclusions: The associations between diagnosis patterns and prescribed acupoints were identified using an online virtual diagnosis modality. Network and text mining analyses revealed commonly applied and disease-specific acupoints in both qualitative and quantitative terms.

scholarly journals Lyric Text Mining Of Dangdut: Visualizing The Selected Words And Word Pairs Of The Legendary Rhoma Irama’s Dangdut Song In The 1970s Era

2018 ◽  
Vol 4 (2) ◽  
pp. 9-17
Author(s):  
Tresna Maulana Fahrudin ◽  
Ali Ridho Barakbah
Keyword(s):  
Text Mining ◽  
Data Extraction ◽  
Way Of Life ◽  
Network Graph ◽  
Human Right ◽  
Inverse Document Frequency ◽  
Document Frequency ◽  
Song Lyrics ◽  
The Relationship ◽  
Word Frequencies

Dangdut is a new genre of music introduced by Rhoma Irama, Indonesian popular musician who was the Legendary dangdut singer in the 1970s era until now. The expression of  Rhoma Irama’s lyric has themes of the human being, the way of life, love, law and human right, tradition, social equality, and Islamic messages. But interestingly, the song lyrics were written by Rhoma Irama in the 1970s were mostly on the love song themes. In order to prove this, it is necessary to identify the songs through several approaches to explore the selected word and the relationship between word pairs. If each Rhoma Irama’s lyric is identified in text mining field, the lyric text extraction will be an interesting knowledge pattern. We collected the lyric from web were used as datasets, and then we have done the data extraction to store the component of lyric including the part and line of the song. We successfully applied the most word frequencies in the form of data visualization including bar chart, word cloud, term frequency-inverse document frequency, and network graph. As a results, several word pairs that often was used by Rhoma Irama in writing his song including heart-love (19 lines), heart-longing (13 lines), heart-beloved (12 lines), love-beloved (12 lines), love-longing (11 lines).

scholarly journals The Analysis of Proximity Between Subjects Based on Primary Contents Using Cosine Similarity on Lective

2017 ◽  
pp. 299-308
Author(s):  
Muhammad Andi Al-rizki ◽  
Galih Wasis Wicaksono ◽  
Yufis Azhar
Keyword(s):  
Cosine Similarity ◽  
High Similarity ◽  
Inverse Document Frequency ◽  
Term Frequency ◽  
Research Results ◽  
Document Frequency ◽  
Precision And Accuracy ◽  
The Relationship ◽  
Similarity Method

In education world, recognizing the relationship between one subject and another is imperative. By recognizing the relationship between courses, performing sustainability mapping between subjects can be easily performed.  Moreover, detecting and reducing any duplicated contents in several subjects will be also possible to execute. Of course, these conveniences will benefit lecturers, students and departments. It will ease the analysis and discussion processes between lecturers related to subjects in the same domain. In addition, students will conveniently choose a group of subjects they are interested in. Furthermore, departments can easily create a specialization group based on the similarity of the subjects and combine the courses possessing high similarity. In this research, given a good database, the relationship between subjects was calculated based on the proximity of the primary contents of the subjects. The feature used was term feature, in which value was determined by calculating TF-IDF (Term Frequency Inverse Document Frequency) from each term. In recognizing the value of proximity between subjects, cosine similarity method was implemented. Finally, testing was done utilizing precision, recall and accuracy method. The research results show that the precision and accuracy values are 90,91% and the recall value is 100%.

scholarly journals Ethical Consumers’ Awareness of Vegan Materials: Focused on Fake Fur and Fake Leather

2021 ◽  
Vol 13 (1) ◽  
pp. 436
Author(s):  
Yeong-Hyeon Choi ◽  
Kyu-Hye Lee
Keyword(s):  
Animal Rights ◽  
Keyword Search ◽  
Animal Abuse ◽  
Ethical Awareness ◽  
Inverse Document Frequency ◽  
Animal Protection ◽  
Ethical Consumers ◽  
Search Volume ◽  
Document Frequency ◽  
The Relationship

With an increase in ethical awareness, people have begun to criticize the unethical issues associated with the use of animal materials. This study focused on the transition of global consumers’ awareness toward vegan materials and the relationship between the interest in ethical subjects such as animals, the environment, and vegan materials. For this purpose, consumers’ posts about fur/fake fur and leather/fake leather uploaded on Google and Twitter from 2008 to 2019 were utilized, and the Term Frequency-Inverse Document Frequency (Tf-idf) value was extracted using Python 3.7. Furthermore, the worldwide Google keyword search volume of each word was analyzed using Smart PLS 3.0 to investigate global consumers’ awareness. First, with time, consumers began relating animal materials such as fur and leather to topics such as animal rights, animal abuse, and animal protection. Second, as interest in “animal welfare” increased, interest in “fake fur” also rose, and as interest in “cruelty free” increased, interest in “fake fur”, “vegan fur”, and “vegan leather” also increased. Third, as consumers’ interest in the “environment” increased, interest in vegan materials such as “fake fur” and “fake leather” decreased. However, as interest in “eco” increased, interest in “vegan leather” also augmented.

scholarly journals Analysis of Matric Product Matching Between Cosine Similarity with Term Frequency-Inverse Document Frequency (TF-IDF) and Word2Vec in PT. Pricebook Digital Indonesia

2020 ◽  
pp. 105-112
Author(s):  
Harni Kusniyati ◽  
Arie Aditya Nugraha
Keyword(s):  
Word Embedding ◽  
Cosine Similarity ◽  
Consumer Experience ◽  
Inverse Document Frequency ◽  
Term Frequency ◽  
Document Frequency ◽  
The Relationship ◽  
Product Specifications ◽  
Similarity Method ◽  
Product Matching

Consumers today have the option to purchase products from thousands of e-commerce. However, the completeness of the product specifications and taxonomies used to organize products differently in different electronic shop differently. To improve the consumer experience, Pricebook approach for integration of the product through the website to find the cheapest price from various platforms. In our writing, we do approach by using a model of neural language such as TF-IDF (term frequency-inverse document frequency) as well as Word2vec by using the method of cosine similarity. TF-IDF is a way to give the relationship a word weighting (term) against the document. Semantic vector or word embedding is one way to represent the structure of a sentence will be in align with manipulating sentences into vector shapes with Word2Vec. Cosine similarity method is a method to calculate the similarity between two objects that is expressed in two vectors by using keywords (keywords) of a document as the size so that it leads to more products matching good performance and categorization. In addition, we compare the results of the representation of the TF-IDF with Word2vec against a number of the data.

Designing a business unit and creating the first ever responsive kitchen

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Paolo FESTA ◽  
Tommaso CORA ◽  
Lucilla FAZIO
Keyword(s):  
Value Creation ◽  
Product Innovation ◽  
Research Laboratory ◽  
Direct Relationship ◽  
Multidisciplinary Approach ◽  
Design Thinking ◽  
Business Unit ◽  
Qualitative And Quantitative Analysis ◽  
Qualitative And Quantitative ◽  
The Relationship

Is it possible to transform stone into a technological and innovative device? The meeting with one of the main stone transformers in Europe produced the intention of a disruptive operation that could affect the strategy of the whole company. A contagious singularity. By intertwining LEAN methodologies and the human-centric approach of design thinking, we mapped the value creation in the company activating a dialogue with the workers and the management, listening to people, asking for ambitions, discovering problems and the potential of production. This qualitative and quantitative analysis conducted with a multidisciplinary approach by designers, architects and marketing strategists allowed us to define a new method. We used it to design a platform that could let all the players express their potential to the maximum. This is how the group's research laboratory was born, with the aim of promoting the relationship between humans and stone through product innovation. With this goal, we coordinated the new team, developing technologies that would allow creating a more direct relationship between man and surface, making the stone reactive. The result was the first responsive kitchen ever.

Terson sign:

2020 ◽  
Vol 2 (1) ◽  
pp. 38-43
Author(s):  
Luiz Severo Bem Junior ◽  
Gustavo De Souza Andrade ◽  
Joao Ribeiro Memória Júnior ◽  
Hildo Rocha Cirne de Azevedo Filho
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Early Recognition ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Case Reports ◽  
Clinical Status ◽  
Vitreous Hemorrhage ◽  
Anterior Communicating Artery ◽  
Inclusion Criteria ◽  
Relationship Of ◽  
The Relationship

Terson's sign (TS) is classically defined as vitreous hemorrhage associated with subarachnoid hemorrhage of aneurysmal origin, being an important predictor of severity, indicating greater morbidity and mortality when compared to patients without the sign. The objective of this study is to review the relationship of Terson syndrome/Terson sign with the prognosis of aneurysmal subarachnoid hemorrhage. A search for original articles, research and case reports was performed on the PubMed, Scielo, Cochrane and ScienceDirect platform, with the following descriptors: Terson sign and subarachnoid hemorrhage. Retrospective, prospective articles and case reports published in the last 5 years and which were in accordance with the established objective and inclusion criteria were selected. Ten (10) articles were selected, in which the available results show an unfavorable prognostic relationship of TS and subarachnoid hemorrhage, because these patients had a worse clinical status assessed on the Glasgow scales ≤ 8, Hunt & Hess > III, Fisher > 3, in addition to intracranial hypertension and location of the aneurysm in the anterior communicating artery complex. The early recognition of this condition described by Albert Terson in 1900 brought an important contribution to neurosurgery, being recognized until nowadays.

Explore the Possible Impact of BCG Vaccination Policy on the Morbidity, Mortality, and Recovery Rates due to COVID-19 Infection. (Preprint)

2020 ◽  
Author(s):  
Yue-Cune Chang
Keyword(s):  
Odds Ratio ◽  
Randomized Clinical Trials ◽  
Vaccination Policy ◽  
Bacille Calmette Guerin ◽  
Recovery Rates ◽  
Bcg Vaccination ◽  
The World ◽  
New Form ◽  
The Relationship ◽  
Disease Specific

BACKGROUND The Coronavirus Disease-19 (COVID-19) is the new form of an acute infectious respiratory disease and has quickly spread over most continents in the world. Recently, it has been shown that Bacille Calmette-Guerin (BCG) might protect against COVID-19. This study aims to investigate the possible correlation between BCG vaccination and morbidity/mortality/recovery rate associated with COVID-19 infection. OBJECTIVE Our findings confirm that the BCG vaccination might protect against COVID-19 virus infection. METHODS Data of COVID-19 confirmed cases, deaths, recoveries, and population were obtained from https://www.worldometers.info/coronavirus/ (Accessed on 12 June, 2020). To have meaningful comparisons among countries’ mortality and recovery rates, we only choose those countries with COVID-19 infected cases at least 200. The Poisson regression and logistic regression were used to explore the relationship between BCG vaccination and morbidity, mortality and recovery rates. RESULTS Among those 158 countries with at least 200 COVID-19 infected cases, there were 141 countries with BCG vaccination information available. The adjusted rates ratio of COVID-19 confirmed cases for Current BCG vaccination vs. non-Current BCG vaccination was 0.339 (with 95% CI= (0.338,0.340)). Moreover, the adjusted odds ratio (OR) of death and recovery after coronavirus infected for Current BCG vaccination vs. non-Current BCG vaccination were 0.258 (with 95% CI= (0.254,0.261)) and 2.151 (with 95% CI= (2.140,2.163)), respectively. CONCLUSIONS That data in this study show the BCG might provide the protection against COVID-19, with consequent less COVID-19 infection and deaths and more rapid recovery. BCG vaccine might bridge the gap before the disease-specific vaccine is developed, but this hypothesis needs to be further tested in rigorous randomized clinical trials. INTERNATIONAL REGISTERED REPORT RR2-https://doi.org/10.1101/2020.06.14.20131268

scholarly journals A Network Analysis of the Relationship among Reading, Spelling and Maths Skills

2021 ◽  
Vol 11 (5) ◽  
pp. 656
Author(s):  
Pierluigi Zoccolotti ◽  
Paola Angelelli ◽  
Chiara Valeria Marinelli ◽  
Daniele Luigi Romano
Keyword(s):  
Network Analysis ◽  
Clinical Analysis ◽  
Skill Learning ◽  
Fifth Grade ◽  
Learning Skills ◽  
Level Model ◽  
Multi Level ◽  
Unselected Group ◽  
The Relationship

Background. Skill learning (e.g., reading, spelling and maths) has been predominantly treated separately in the neuropsychological literature. However, skills (as well as their corresponding deficits), tend to partially overlap. We recently proposed a multi-level model of learning skills (based on the distinction among competence, performance, and acquisition) as a framework to provide a unitary account of these learning skills. In the present study, we examined the performance of an unselected group of third- to fifth-grade children on standard reading, spelling, and maths tasks, and tested the relationships among these skills with a network analysis, i.e., a method particularly suited to analysing relations among different domains. Methods. We administered a battery of reading, spelling, and maths tests to 185 third-, fourth-, and fifth-grade children (103 M, 82 F). Results. The network analysis indicated that the different measures of the same ability (i.e., reading, spelling, and maths) formed separate clusters, in keeping with the idea that they are based on different competences. However, these clusters were also related to each other, so that three nodes were more central in connecting them. In keeping with the multi-level model of learning skills, two of these tests (arithmetic facts subtest and spelling words with ambiguous transcription) relied heavily on the ability to recall specific instances, a factor hypothesised to underlie the co-variation among learning skills. Conclusions. The network analysis indicated both elements of association and of partial independence among learning skills. Interestingly, the study was based on standard clinical instruments, indicating that the multi-level model of learning skills might provide a framework for the clinical analysis of these learning skills.

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