Face Mask Controls and Duration of Wearing: What Medical Research Can Teach the Cleanroom Manager

2021 ◽  
Vol 25 (3) ◽  
Author(s):  
Tim Sandle
Keyword(s):  
Medical Research ◽  
Face Mask ◽  
Medical Field ◽  
Contamination Control ◽  
Filter Efficiency ◽  
User Comfort

No mask is 100% effective. Masks are a tradeoff between bacterial and particle efficiency and user comfort, with a 97.5% bacterial filter efficiency the typical rating. Achieving this is dependent upon the mask integrity and worn correctly. This paper covers cleanroom contamination control, more recent research within the medical field has been driven by responses to the coronavirus, and some recommendations for the control of surgical face masks worn in cleanrooms.

Editor Note Volume 3 Issue 1

2021 ◽  
Author(s):  
Ian James Martins
Keyword(s):  
Animal Models ◽  
Pulmonary Tuberculosis ◽  
Medical Research ◽  
Data Analytics ◽  
Healthcare Professionals ◽  
Scientific Process ◽  
Medical Field ◽  
Medical Researchers ◽  
Research Questions ◽  
High Standards

The articles published in Volume 3, Issue 1 maintain the high standards for peer-reviewed journals. These articles are related to Pulmonary Tuberculosis, Animal Models, COVID-19 vaccines, Dentistry Data Analytics, and the Psychosocial Impact of COVID-19 in children. The effort and expertise of these authors contribute to clinical and medical research and is the cornerstone of the scientific process with relevance to peer-review by medical researchers and healthcare professionals. The research questions in these articles are important and appropriate to the journal and adhere to journal standards and to the top 10% of papers published in the medical field.

scholarly journals Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed

10.2196/16816 ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. e16816 ◽  
Author(s):  
Jing Wang ◽  
Huan Deng ◽  
Bangtao Liu ◽  
Anbin Hu ◽  
Jun Liang ◽  
...  
Keyword(s):  
United States ◽  
Systematic Review ◽  
Natural Language Processing ◽  
Natural Language ◽  
Medical Research ◽  
Language Processing ◽  
The United States ◽  
Columbia University ◽  
Medical Field ◽  
Number Of Publications

Background Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing importance of understanding and mining big data in the medical field, NLP is becoming more crucial. Objective The goal of the research was to perform a systematic review on the use of NLP in medical research with the aim of understanding the global progress on NLP research outcomes, content, methods, and study groups involved. Methods A systematic review was conducted using the PubMed database as a search platform. All published studies on the application of NLP in medicine (except biomedicine) during the 20 years between 1999 and 2018 were retrieved. The data obtained from these published studies were cleaned and structured. Excel (Microsoft Corp) and VOSviewer (Nees Jan van Eck and Ludo Waltman) were used to perform bibliometric analysis of publication trends, author orders, countries, institutions, collaboration relationships, research hot spots, diseases studied, and research methods. Results A total of 3498 articles were obtained during initial screening, and 2336 articles were found to meet the study criteria after manual screening. The number of publications increased every year, with a significant growth after 2012 (number of publications ranged from 148 to a maximum of 302 annually). The United States has occupied the leading position since the inception of the field, with the largest number of articles published. The United States contributed to 63.01% (1472/2336) of all publications, followed by France (5.44%, 127/2336) and the United Kingdom (3.51%, 82/2336). The author with the largest number of articles published was Hongfang Liu (70), while Stéphane Meystre (17) and Hua Xu (33) published the largest number of articles as the first and corresponding authors. Among the first author’s affiliation institution, Columbia University published the largest number of articles, accounting for 4.54% (106/2336) of the total. Specifically, approximately one-fifth (17.68%, 413/2336) of the articles involved research on specific diseases, and the subject areas primarily focused on mental illness (16.46%, 68/413), breast cancer (5.81%, 24/413), and pneumonia (4.12%, 17/413). Conclusions NLP is in a period of robust development in the medical field, with an average of approximately 100 publications annually. Electronic medical records were the most used research materials, but social media such as Twitter have become important research materials since 2015. Cancer (24.94%, 103/413) was the most common subject area in NLP-assisted medical research on diseases, with breast cancers (23.30%, 24/103) and lung cancers (14.56%, 15/103) accounting for the highest proportions of studies. Columbia University and the talents trained therein were the most active and prolific research forces on NLP in the medical field.

scholarly journals Medical Research Volunteer Program (MRVP): innovative program promoting undergraduate research in the medical field

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Michael M. Dagher ◽  
Jessica A. Atieh ◽  
Marwa K. Soubra ◽  
Samia J. Khoury ◽  
Hani Tamim ◽  
...  
Keyword(s):  
Medical Research ◽  
Undergraduate Research ◽  
Medical Field ◽  
Volunteer Program ◽  
Innovative Program

Induction of Hypotheses Concerning Hip Arthroplasty: A Modified Methodology for Medical Research

2001 ◽  
Vol 40 (05) ◽  
pp. 392-396 ◽  
Author(s):  
I. Bratko ◽  
J. Demšar ◽  
D. Smrke ◽  
V. Stankovski
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Medical Research ◽  
Hip Arthroplasty ◽  
Statistical Tests ◽  
Medical Problem ◽  
Medical Field ◽  
Neck Fracture ◽  
Machine Learning Tool

Summary Objectives: The objective of this study is to advocate a methodology for medical research that, in contrast to traditional medical methodology, exploits the flexibility of machine learning and retains the kind of statistical tests that are generally accepted in the medical field for the confirmation of hypotheses. Methods: First, the medical problem is defined and data for an observed population are collected; then a machine learning tool is used to generate hypotheses regarding the problem; finally, statistical methods are used to determine the validity of the generated hypotheses. Results: To illustrate this approach, the problem of defining indications for hip arthroplasty after an acute medial femoral neck fracture is investigated as a case study. Conclusions: The methodology is similar to the usual style of applying machine learning, but insists on a link to the techniques of statistical tests that are normally used in medicine. It aims at a more flexible and economical use of experimental data than in the usual medical research, which is enabled by techniques of machine learning. At the same time, by reference to traditional statistical tests, it is hoped that this approach will lead to improved acceptance of machine learning in the medical field.

‘Kachinja are Coming!’: Encounters Around Medical Research Work in a Kenyan Village

Africa ◽  
2005 ◽  
Vol 75 (2) ◽  
pp. 173-202 ◽  
Author(s):  
P. Wenzel Geissler
Keyword(s):  
Medical Research ◽  
Social Relations ◽  
Social Practice ◽  
Research Work ◽  
Field Research ◽  
Social Situations ◽  
Medical Field ◽  
Western Kenya ◽  
Local Patterns

AbstractWhen conducting medical field research in a Luo village in western Kenya, my colleagues and I were occasionally suspected of being blood-thieves, locally called kachinja. The article contextualizes these blood-stealing accusations within the practices of medical research that prompted them, and within the local historical experiences which, I shall argue, they refer to. Further, it examines two social situations, in which blood-stealing accusations were raised against me and people who were in contact with me, in order to show how the kachinja idiom is used in social practice, as part of long-term social processes as well as of momentary situations, within local patterns of relatedness. These observations show how global structures and processes are articulated and moulded in a particular locality through idioms that carry memories of individual as well as collective, historical experiences, and how they are enacted by people within webs of contemporary local social relations.

scholarly journals Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed (Preprint)

2019 ◽  
Author(s):  
Jing Wang ◽  
Huan Deng ◽  
Bangtao Liu ◽  
Anbin Hu ◽  
Jun Liang ◽  
...  
Keyword(s):  
United States ◽  
Systematic Review ◽  
Natural Language Processing ◽  
Natural Language ◽  
Medical Research ◽  
Language Processing ◽  
The United States ◽  
Columbia University ◽  
Medical Field ◽  
Number Of Publications

BACKGROUND Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing importance of understanding and mining big data in the medical field, NLP is becoming more crucial. OBJECTIVE The goal of the research was to perform a systematic review on the use of NLP in medical research with the aim of understanding the global progress on NLP research outcomes, content, methods, and study groups involved. METHODS A systematic review was conducted using the PubMed database as a search platform. All published studies on the application of NLP in medicine (except biomedicine) during the 20 years between 1999 and 2018 were retrieved. The data obtained from these published studies were cleaned and structured. Excel (Microsoft Corp) and VOSviewer (Nees Jan van Eck and Ludo Waltman) were used to perform bibliometric analysis of publication trends, author orders, countries, institutions, collaboration relationships, research hot spots, diseases studied, and research methods. RESULTS A total of 3498 articles were obtained during initial screening, and 2336 articles were found to meet the study criteria after manual screening. The number of publications increased every year, with a significant growth after 2012 (number of publications ranged from 148 to a maximum of 302 annually). The United States has occupied the leading position since the inception of the field, with the largest number of articles published. The United States contributed to 63.01% (1472/2336) of all publications, followed by France (5.44%, 127/2336) and the United Kingdom (3.51%, 82/2336). The author with the largest number of articles published was Hongfang Liu (70), while Stéphane Meystre (17) and Hua Xu (33) published the largest number of articles as the first and corresponding authors. Among the first author’s affiliation institution, Columbia University published the largest number of articles, accounting for 4.54% (106/2336) of the total. Specifically, approximately one-fifth (17.68%, 413/2336) of the articles involved research on specific diseases, and the subject areas primarily focused on mental illness (16.46%, 68/413), breast cancer (5.81%, 24/413), and pneumonia (4.12%, 17/413). CONCLUSIONS NLP is in a period of robust development in the medical field, with an average of approximately 100 publications annually. Electronic medical records were the most used research materials, but social media such as Twitter have become important research materials since 2015. Cancer (24.94%, 103/413) was the most common subject area in NLP-assisted medical research on diseases, with breast cancers (23.30%, 24/103) and lung cancers (14.56%, 15/103) accounting for the highest proportions of studies. Columbia University and the talents trained therein were the most active and prolific research forces on NLP in the medical field.

scholarly journals Knowledge, attitude and practices towards medical research among resident doctors at a tertiary care hospital

2019 ◽  
Vol 8 (11) ◽  
pp. 2517
Author(s):  
Rajshree N. Mandhare ◽  
Venkatesh V. Khadke ◽  
Saleem B. Tamboli
Keyword(s):  
Medical Research ◽  
Tertiary Care ◽  
Research Process ◽  
Basic Knowledge ◽  
P Value ◽  
Care Hospital ◽  
Medical Field ◽  
Spss Software ◽  
Knowledge Attitude And Practice ◽  
Structured Questionnaire

Background: Research is a systematic process utilizing the scientific method for generating new knowledge that can be used to solve a problem or improving the existing status of a system. Human being is living a life of ease due to research in medical field. But it is important to know that whether those who are closest to society like resident doctors are involved in research process or not. Thus, the present study is planned to assess the knowledge, attitude and practice of resident doctors in a tertiary care hospital.Methods: This was the questionnaire-based study conducted among the resident doctors. Sample size calculated was 110 by open Epi software. A self-structured questionnaire was validated and distributed. Then we collected the data which was analysed using statistical analysis with MS excel and SPSS software version 21.Results: The 62% response rate was achieved. More than 50% of the resident doctors have the knowledge of p value and protocol writing. 63% students are strongly agreed that research in medical field is important while only 19% students are strongly disagreed that research increases burden over students 17% of the students have presented research paper. More than 75% student told that there are many barriers conducting research.Conclusions: This study demonstrates that more than 50% respondents have the basic knowledge about the medical research and they have the positive attitude too. But there is lack of the practices regarding research. Thus, there should be some efforts to improve practices of medical research among resident doctors.

A stochastic SIR model for analysis of testosterone suppression of CRH-stimulated cortisol in men

2021 ◽  
Author(s):  
A. Manickam ◽  
Pushpendra Kumar ◽  
K. Dasunaidu ◽  
V. Govindaraj ◽  
Dheeraj Kumar Joshi
Keyword(s):  
Mathematical Model ◽  
Medical Research ◽  
Hpa Axis ◽  
Sir Model ◽  
Transmission Model ◽  
Medical Field ◽  
Sir Epidemic ◽  
Stochastic Sir ◽  
Stochastic Sir Model ◽  
The Given

A stochastic SIR influenza vertical transmission model is examined in this paper where vaccination and an incidence rate that is not linear are considered. To determine whether testosterone regulates lower sintering HPA axis function in males, we used a stochastic SIR epidemic procedure with divergent influences on ACTH and cortisol. The suppressive effects on cortisol can be attributed to a peripheral (adrenal) locus. Following that, we came to the conclusion that experimental solutions have been discovered and the requisite statistical findings have been examined. Finally, we deduce that the given mathematical model and the results are relevant to medical research. In the future, this research can be further extended to simulate more results in the medical field.

Application of Latent Curve Models in Medical Research - A Review

2009 ◽  
Vol 4 (2) ◽  
pp. 52
Author(s):  
Jun-Hao Pan ◽  
Xin-Yuan Song ◽  
Timothy Kwok ◽  
◽  
◽  
...  
Keyword(s):  
Medical Research ◽  
Fundamental Principle ◽  
Statistical Technique ◽  
Medical Applications ◽  
Individual Change ◽  
Medical Field ◽  
Latent Curve ◽  
Latent Curve Models ◽  
The Relationship ◽  
Over Time

Recently, latent curve modelling (LCM) has received increasing attention in the analysis of longitudinal data. It is a method to model individual change and to assess the effects of co-variates and the relationship among multiple outcomes. It provides an integrated and flexible approach in modelling developmental processes from both inter- and intra-individual perspectives. Similar to conventional longitudinal analysis, the main objectives of this model are to characterise changes in the response of interest over time and to examine the selected covariates that contribute to those changes. In this article the fundamental principle of LCM is briefly introduced. Several important kinds of LCM, including linear LCM, non-linear LCM, multilevel LCM and mixture LCM, together with their applications in medical research, are reviewed. We believe that this statistical technique should become more popular in medical applications, and that the medical field would benefit from increased use of this powerful and flexible statistical method.

scholarly journals Awareness of Medical Research Ethics among Medical students

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Sudheendra Kulkarni ◽  
Kumar Sai Sailesh ◽  
Chandrakant Chillarge
Keyword(s):  
Medical Students ◽  
Medical Research ◽  
Research Ethics ◽  
Female Students ◽  
Medical Council ◽  
Medical Sciences ◽  
Medical Field ◽  
Standard Questionnaire ◽  
Medical Research Ethics

The present study was carried out to observe the knowledge of Medical research ethics among medical students. The study was conducted in the Department of Microbiology, Bidar Institute of Medical sciences, Bidar. 200 male (n=100) and female (n=100) second, third & final year MBBS students were included in the study. The standard questionnaire was used to assess participants' knowledge in research ethics. Knowledge of both male andfemalestudentsregardingresearchethics.Inourstudywehaveobservedthat veryfewstudentshasknowledgeabouttheresearchethics.However, comparatively female students are having better knowledge about research ethics than males. We conclude that overall knowledge about Medical research ethics in medical students was very poor and there is a need to introduce research ethics as one mandatory subject in medical syllabus, as research ethics has applicability. Medical council of India must consider this aspect and introduce a Research ethics department in Medical field along with other departments.

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