scholarly journals TREASURE: Text Mining Algorithm Based On Affinity Analysis and Set Intersection to Find the Action of Tuberculosis Drugs against Other Pathogens

2021 ◽  
Vol 11 (15) ◽  
pp. 6834
Author(s):  
Pradeepa Sampath ◽  
Nithya Shree Sridhar ◽  
Vimal Shanmuganathan ◽  
Yangsun Lee
Keyword(s):  
Text Mining ◽  
Causes Of Death ◽  
Intersection Property ◽  
Research Papers ◽  
Bacterial Diseases ◽  
Mining Algorithm ◽  
Set Intersection ◽  
The World ◽  
Medical Researchers

Tuberculosis (TB) is one of the top causes of death in the world. Though TB is known as the world’s most infectious killer, it can be treated with a combination of TB drugs. Some of these drugs can be active against other infective agents, in addition to TB. We propose a framework called TREASURE (Text mining algoRithm basEd on Affinity analysis and Set intersection to find the action of tUberculosis dRugs against other pathogEns), which particularly focuses on the extraction of various drug–pathogen relationships in eight different TB drugs, namely pyrazinamide, moxifloxacin, ethambutol, isoniazid, rifampicin, linezolid, streptomycin and amikacin. More than 1500 research papers from PubMed are collected for each drug. The data collected for this purpose are first preprocessed, and various relation records are generated for each drug using affinity analysis. These records are then filtered based on the maximum co-occurrence value and set intersection property to obtain the required inferences. The inferences produced by this framework can help the medical researchers in finding cures for other bacterial diseases. Additionally, the analysis presented in this model can be utilized by the medical experts in their disease and drug experiments.

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

scholarly journals Mortality beyond emergency threshold in a silent crisis– results from a population-based mortality survey in Ouaka prefecture, Central African Republic, 2020

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Eve Robinson ◽  
Lawrence Lee ◽  
Leslie F. Roberts ◽  
Aurelie Poelhekke ◽  
Xavier Charles ◽  
...  
Keyword(s):  
Central African Republic ◽  
Causes Of Death ◽  
Maternal Mortality Ratio ◽  
Mortality Rates ◽  
Population Based ◽  
Access To Healthcare ◽  
Mortality Data ◽  
Humanitarian Emergency ◽  
The World ◽  
Mortality Survey

Abstract Background The Central African Republic (CAR) suffers a protracted conflict and has the second lowest human development index in the world. Available mortality estimates vary and differ in methodology. We undertook a retrospective mortality study in the Ouaka prefecture to obtain reliable mortality data. Methods We conducted a population-based two-stage cluster survey from 9 March to 9 April, 2020 in Ouaka prefecture. We aimed to include 64 clusters of 12 households for a required sample size of 3636 persons. We assigned clusters to communes proportional to population size and then used systematic random sampling to identify cluster starting points from a dataset of buildings in each commune. In addition to the mortality survey questions, we included an open question on challenges faced by the household. Results We completed 50 clusters with 591 participating households including 4000 household members on the interview day. The median household size was 7 (interquartile range (IQR): 4—9). The median age was 12 (IQR: 5—27). The birth rate was 59.0/1000 population (95% confidence interval (95%-CI): 51.7—67.4). The crude and under-five mortality rates (CMR & U5MR) were 1.33 (95%-CI: 1.09—1.61) and 1.87 (95%-CI: 1.37–2.54) deaths/10,000 persons/day, respectively. The most common specified causes of death were malaria/fever (16.0%; 95%-CI: 11.0–22.7), violence (13.2%; 95%-CI: 6.3–25.5), diarrhoea/vomiting (10.6%; 95%-CI: 6.2–17.5), and respiratory infections (8.4%; 95%-CI: 4.6–14.8). The maternal mortality ratio (MMR) was 2525/100,000 live births (95%-CI: 825—5794). Challenges reported by households included health problems and access to healthcare, high number of deaths, lack of potable water, insufficient means of subsistence, food insecurity and violence. Conclusions The CMR, U5MR and MMR exceed previous estimates, and the CMR exceeds the humanitarian emergency threshold. Violence is a major threat to life, and to physical and mental wellbeing. Other causes of death speak to poor living conditions and poor access to healthcare and preventive measures, corroborated by the challenges reported by households. Many areas of CAR face similar challenges to Ouaka. If these results were generalisable across CAR, the country would suffer one of the highest mortality rates in the world, a reminder that the longstanding “silent crisis” continues.

scholarly journals A Decision-Making Approach Based on TOPSIS Method for Ranking Smart Cities in the Context of Urban Energy

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2691
Author(s):  
Sławomira Hajduk ◽  
Dorota Jelonek
Keyword(s):  
Decision Making ◽  
Smart Cities ◽  
Energy Performance ◽  
Linear Ordering ◽  
Topsis Method ◽  
Research Papers ◽  
The World ◽  
Urban Energy ◽  
World Council ◽  
Topsis Technique

This paper presents the use of multi-criteria decision-making (MCDM) for the evaluation of smart cities. During the development of the method, the importance of the decision-making approach in the linear ordering of cities was presented. The method of using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was proposed for the preparation of ranking. The method was verified by the application in the measurement of energy performance in smart cities. The authors conducted a literature review of research papers related to urban energy and MCDM published in the period from 2010 to 2020. The paper uses data from the World Council on City Data (WCCD). The research conducted allowed for the identification of the most popular MCDM techniques in the field of urban energy such as TOPSIS, AHP and DEA. The TOPSIS technique was used to organize and group the analyzed cities. Porto took the top position, whereas Buenos Aries was the last.

scholarly journals Carbon Dots for Cancer Nanomedicine: A Bright Future

2021 ◽  
Author(s):  
Samer Bayda ◽  
Emanuele Amadio ◽  
Simone Cailotto ◽  
Yahima Frión-Herrera ◽  
Alvise Perosa ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Carbon Dots ◽  
Causes Of Death ◽  
Cancer Therapies ◽  
Therapeutic Approaches ◽  
Bright Future ◽  
Cancer Nanomedicine ◽  
The World

Cancer remains one of the main causes of death in the world. Early diagnosis and effective cancer therapies are required to treat this pathology. Traditional therapeutic approaches are limited by...

scholarly journals Identification of Bacterial Diseases in Rice Plants Leaves by the Use of Spectroscopic Imaging

2015 ◽  
Vol 7 (6) ◽  
pp. 61 ◽  
Author(s):  
Mama Sangare ◽  
C. Tekete ◽  
O. K. Bagui ◽  
A. Ba ◽  
J. T. Zoueu
Keyword(s):  
Statistical Analysis ◽  
Bacterial Wilt ◽  
Spectral Region ◽  
Imaging Techniques ◽  
Xanthomonas Oryzae ◽  
Multivariate Statistical ◽  
Bacterial Diseases ◽  
The World ◽  
Rice Leaves ◽  
Statistical Analysis Methods

<p class="1Body">Rice is staple in the African habitats menu. Bacterial wilt (BLB) and leaf streak (BLS) are some of the phytopathological diseases which restrain rice production around the world. In this paper, multi-spectral and multi-modal imaging techniques have been developed to characterize the rice leaves with symptoms of bacterial wilt (BLB) and leaf streak (BLS), and to provide information on their effects, in order to reduce their spread. First, we recorded microscopic and spectroscopic images of the samples using multimodal and multispectral microscope, with spectral region ranging from UV to NIR, for each mode. Then, we extracted the spectral footprints of the cells constituents, in transmission, reflection and scattering from the spectral images. Applying multivariate statistical analysis methods to this optical spectra allowed us to characterize the effect of bacterial rice leaves caused by <em>Xanthomonas oryzae</em> strains. The results of the proposed technique can be useful for easy identification of this type of infection, and can serve as routine approach in biochemical and agronomic laboratories.</p>

scholarly journals Causes of Mortality in Older People With Intellectual Disability: Results From the HA-ID Study

2018 ◽  
Vol 123 (1) ◽  
pp. 61-71 ◽  
Author(s):  
Alyt Oppewal ◽  
Josje D. Schoufour ◽  
Hanne J.K. van der Maarl ◽  
Heleen M. Evenhuis ◽  
Thessa I.M. Hilgenkamp ◽  
...  
Keyword(s):  
Older Adults ◽  
Intellectual Disability ◽  
Cause Of Death ◽  
Causes Of Death ◽  
Circulatory System ◽  
Bacterial Diseases ◽  
Specific Mortality ◽  
Causes Of Mortality ◽  
Insight Into

Abstract We aim to provide insight into the cause-specific mortality of older adults with intellectual disability (ID), with and without Down syndrome (DS), and compare this to the general population. Immediate and primary cause of death were collected through medical files of 1,050 older adults with ID, 5 years after the start of the Healthy Ageing and Intellectual Disabilities (HA-ID) study. During the follow-up period, 207 (19.7%) participants died, of whom 54 (26.1%) had DS. Respiratory failure was the most common immediate cause of death (43.4%), followed by dehydration/malnutrition (20.8%), and cardiovascular diseases (9.4%). In adults with DS, the most common cause was respiratory disease (73.3%), infectious and bacterial diseases (4.4%), and diseases of the digestive system (4.4%). Diseases of the respiratory system also formed the largest group of primary causes of death (32.1%; 80.4% was due to pneumonia), followed by neoplasms (17.6%), and diseases of the circulatory system (8.2%). In adults with DS, the main primary cause was also respiratory diseases (51.1%), followed by dementia (22.2%).

scholarly journals Ten Famous Composers of the Romantic Era and their Cause of Death

2021 ◽  
Author(s):  
Ernest K.J. Pauwels
Keyword(s):  
Medical Research ◽  
Cause Of Death ◽  
21St Century ◽  
Causes Of Death ◽  
Human Life ◽  
Modern Medicine ◽  
Expression Of Emotion ◽  
The World ◽  
Romantic Era ◽  
Clinically Significant

The musical composers in the Romantic Era (1800-1910) strived for compositions that expressed human life, including happiness, harmony and despair. They lived in a period in which freedom of thinking, expression of emotion and inspiration by nature predominate. During this period, intensive trading with other parts of the world brought new microorganisms along, which made infections and epidemics very common. This article serves to address the cause of death and relevant biographic data of a number of well- known Romantic composers. Primarily, this review refers to clinically significant findings using reports that were retrieved from Pubmed, Embase and Google over the 19th, 20th and 21st century till 14th June 2021. Here, this text dwells on diseases and the cause of death of ten composers, namely Mozart, Beethoven, Chopin, Schubert, Schumann, Mendelssohn, Brahms, Liszt, Mahler and Bruckner. It is evident that, in the sight of modern medicine, symptoms and forensic facts are not complete, but witnesses' reports and recent medical research have provided passable and plausible clarity. Although many questions will remain unanswered, it appears that the diseases of these composers and their causes of death have their origins in alcohol abuses, age, epidemics (like tuberculosis) and syphilis.

scholarly journals Analysing Tuberculosis Trends in South Asia

2018 ◽  
Vol 8 (6) ◽  
pp. 5245
Author(s):  
Kumar Abhishek ◽  
M. P Singh ◽  
Md. Sadik Hussain
Keyword(s):  
Sri Lanka ◽  
World Health Organization ◽  
South Asia ◽  
Causes Of Death ◽  
Temporal Variations ◽  
World Health ◽  
Spatial And Temporal Variations ◽  
The World ◽  
Health Organization ◽  
The Relationship

<p>Tuberculosis (TB) has been one of the top ten causes of death in the world. As per the World Health Organization (WHO) around 1.8 million people have died due to tuberculosis in 2015. This paper aims to investigate the spatial and temporal variations in TB incident in South Asia (India, Bangladesh, Pakistan, Maldives, Nepal, and Sri-Lanka). Asia had been counted for the largest number of new TB cases in 2015. The paper underlines and relates the relationship between various features like gender, age, location, occurrence, and mortality due to TB in these countries for the period 1993-2012.</p>

scholarly journals SUPPORTING AIR TRANSPORT POLICIES USING BIG DATA ANALYTICS: A DESCRIPTIVE APPROACH BASED EMERGING TREND ANALYSIS

2017 ◽  
Vol 8 (1) ◽  
pp. 51-72
Author(s):  
Jin-seo Park
Keyword(s):  
Qualitative Research ◽  
Big Data ◽  
Text Mining ◽  
Research Methods ◽  
Qualitative Research Methods ◽  
Research Papers ◽  
Emerging Trends ◽  
The Future ◽  
Descriptive Approach ◽  
Core Issues

Qualitative research methods based on literature review or expert judgement have been used to find core issues, analyze emerging trends and discover promising areas for the future. Deriving results from large amounts of information under this approach is both costly and time consuming. Besides, there is a risk that the results may be influenced by the subjective opinion of experts. In order to make up for such weaknesses, the analysis paradigm for choosing future emerging trend is undergoing a shift toward mplementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The hange used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and the promising areas for the future from research papers pertaining to overall aviation areas through text mining method, which is one of the big data analysis techniques. This study has limitations in that its analysis for retrieving the aviation-related core issues and promising fields was restricted to research papers containing the keyword "aviation." However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and emerging trends regarding the promising areas for the future in the aviation industry through the application of a big data-based descriptive approach.

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