Example of IRBM format
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Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format
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Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format Example of IRBM format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access

IRBM — Template for authors

Publisher: Elsevier
Categories Rank Trend in last 3 yrs
Biomedical Engineering #122 of 229 up up by 1 rank
Biophysics #73 of 131 up up by 8 ranks
journal-quality-icon Journal quality:
Medium
calendar-icon Last 4 years overview: 169 Published Papers | 543 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 06/06/2020
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Related Journals

open access Open Access

The Royal Society

Quality:  
High
CiteRatio: 6.6
SJR: 1.655
SNIP: 1.709
open access Open Access
recommended Recommended

The Royal Society

Quality:  
High
CiteRatio: 7.3
SJR: 1.1
SNIP: 1.222
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 4.3
SJR: 0.826
SNIP: 1.318
open access Open Access

IOP Publishing

Quality:  
Good
CiteRatio: 5.0
SJR: 0.674
SNIP: 1.216

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

1.022

9% from 2018

Impact factor for IRBM from 2016 - 2019
Year Value
2019 1.022
2018 0.934
2017 0.897
2016 0.77
graph view Graph view
table view Table view

3.2

60% from 2019

CiteRatio for IRBM from 2016 - 2020
Year Value
2020 3.2
2019 2.0
2018 1.8
2017 1.9
2016 2.1
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 9% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 60% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.346

21% from 2019

SJR for IRBM from 2016 - 2020
Year Value
2020 0.346
2019 0.286
2018 0.246
2017 0.298
2016 0.27
graph view Graph view
table view Table view

0.79

46% from 2019

SNIP for IRBM from 2016 - 2020
Year Value
2020 0.79
2019 0.541
2018 0.635
2017 0.715
2016 0.593
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 21% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 46% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
IRBM

Guideline source: View

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Elsevier

IRBM

IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine Alliance pour le genie biologique et medical) and the SFGBM (BioMedical Engineering French Society / Societe francaise de genie biologique medical) and the AFIB (French Association of Biomedical E...... Read More

Engineering

i
Last updated on
06 Jun 2020
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ISSN
1959-0318
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Impact Factor
Medium - 0.607
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Acceptance Rate
Not provided
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Frequency
Not provided
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Open Access
Yes
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Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
elsarticle-num
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Citation Type
Numbered
[25]
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Bibliography Example
G. E. Blonder, M. Tinkham, T. M. Klapwijk, Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion, Phys. Rev. B 25 (7) (1982) 4515–4532. URL 10.1103/PhysRevB.25.4515

Top papers written in this journal

Journal Article DOI: 10.1016/J.IRBM.2013.01.010
TeleOphta: Machine learning and image processing methods for teleophthalmology
01 Apr 2013 - Irbm

Abstract:

A complete prototype for the automatic detection of normal examinations on a teleophthalmology network for diabetic retinopathy screening is presented. The system combines pathological pattern mining methods, with specific lesion detection methods, to extract information from the images. This information, plus patient and oth... A complete prototype for the automatic detection of normal examinations on a teleophthalmology network for diabetic retinopathy screening is presented. The system combines pathological pattern mining methods, with specific lesion detection methods, to extract information from the images. This information, plus patient and other contextual data, is used by a classifier to compute an abnormality risk. Such a system should reduce the burden on readers on teleophthalmology networks. read more read less

Topics:

Teleophthalmology (62%)62% related to the paper
316 Citations
open accessOpen access Journal Article DOI: 10.1016/J.IRBM.2020.05.003
Deep Transfer Learning Based Classification Model for COVID-19 Disease.
Yadunath Pathak1, Piyush Kumar Shukla, Akhilesh Tiwari2, S. Stalin3, Saurabh Singh4
20 May 2020 - Irbm

Abstract:

The COVID-19 infection is increasing at a rapid rate, with the availability of limited number of testing kits. Therefore, the development of COVID-19 testing kits is still an open area of research. Recently, many studies have shown that chest Computed Tomography (CT) images can be used for COVID-19 testing, as chest CT images... The COVID-19 infection is increasing at a rapid rate, with the availability of limited number of testing kits. Therefore, the development of COVID-19 testing kits is still an open area of research. Recently, many studies have shown that chest Computed Tomography (CT) images can be used for COVID-19 testing, as chest CT images show a bilateral change in COVID-19 infected patients. However, the classification of COVID-19 patients from chest CT images is not an easy task as predicting the bilateral change is defined as an ill-posed problem. Therefore, in this paper, a deep transfer learning technique is used to classify COVID-19 infected patients. Additionally, a top-2 smooth loss function with cost-sensitive attributes is also utilized to handle noisy and imbalanced COVID-19 dataset kind of problems. Experimental results reveal that the proposed deep transfer learning-based COVID-19 classification model provides efficient results as compared to the other supervised learning models. read more read less

Topics:

Transfer of learning (88%)88% related to the paper, Deep learning (67%)67% related to the paper, Computer science (60%)60% related to the paper, Supervised learning (53%)53% related to the paper, Transfer of learning (51%)51% related to the paper
297 Citations
Journal Article DOI: 10.1016/J.IRBM.2008.08.002
A proposal for the classification and evaluation of fall detectors
Norbert Noury1, Norbert Noury2, P. Rumeau2, Alan K. Bourke, Gearóid ÓLaighin3, Jean-Eric Lundy
01 Dec 2008 - Irbm

Abstract:

Falls affect, each year, tens of million of elderly people throughout the world. It can have immediate lethal consequences but also causes many disabling fractures and dramatic psychological consequences which reduce the independence of the person. Falls in the elderly is thus a major public health problem. The “early” detect... Falls affect, each year, tens of million of elderly people throughout the world. It can have immediate lethal consequences but also causes many disabling fractures and dramatic psychological consequences which reduce the independence of the person. Falls in the elderly is thus a major public health problem. The “early” detection of fall consequently raises the interest of searchers, as most of elderly fallers cannot return to a standing position on their own following a fall. It is also an interesting scientific problem because it is an ill-defined process. The goals of this study were to classify various approaches used to detect the fall and to point out the difficulty to compare the results of these studies, as there is currently no common evaluation benchmark. read more read less

Topics:

Poison control (51%)51% related to the paper
252 Citations
Journal Article DOI: 10.1016/J.IRBM.2014.07.002
A review of methods for non-invasive and continuous blood pressure monitoring: Pulse transit time method is promising?
Lukas Peter1, Norbert Noury2, Martin Cerny1
01 Oct 2014 - Irbm

Abstract:

Most medical examinations include measuring of blood pressure because it is a very good indicator about the status of the cardiovascular system, and it helps medical doctors to adjust the ideal treatment. It would be very useful to know the profile of pressure values during long time period, especially during standard daily a... Most medical examinations include measuring of blood pressure because it is a very good indicator about the status of the cardiovascular system, and it helps medical doctors to adjust the ideal treatment. It would be very useful to know the profile of pressure values during long time period, especially during standard daily activities. It could be used for homecare monitoring and prevention of premature death. Problem is that blood pressure is monitored mainly at discrete time intervals and use an inflatable cuff placed around the arm, which is uncomfortable for the patient. Currently, there are a few technical solutions for continuous non-invasive measurement of blood pressure. This review is focused on the description of methods for continuous blood pressure measurement including their limitations and especially is focused on the description method based on pulse transit time. This method could be the most widely used of methods for non-invasive long time monitoring of blood pressure in the future but now there are still a lot of unsolved problems. read more read less
230 Citations
open accessOpen access Journal Article DOI: 10.1016/J.IRBM.2020.07.001
Automated Deep Transfer Learning-Based Approach for Detection of COVID-19 Infection in Chest X-rays.
N. Narayan Das1, Sumera Azam2, Naresh Kumar3, Manjit Kaur1, Vijay Kumar4, Dilbag Singh1
03 Jul 2020 - Irbm

Abstract:

The most widely used novel coronavirus (COVID-19) detection technique is a real-time polymerase chain reaction (RT-PCR) However, RT-PCR kits are costly and take 6-9 hours to confirm infection in the patient Due to less sensitivity of RT-PCR, it provides high false-negative results To resolve this problem, radiological imaging... The most widely used novel coronavirus (COVID-19) detection technique is a real-time polymerase chain reaction (RT-PCR) However, RT-PCR kits are costly and take 6-9 hours to confirm infection in the patient Due to less sensitivity of RT-PCR, it provides high false-negative results To resolve this problem, radiological imaging techniques such as chest X-rays and computed tomography (CT) are used to detect and diagnose COVID-19 In this paper, chest X-rays is preferred over CT scan The reason behind this is that X-rays machines are available in most of the hospitals X-rays machines are cheaper than the CT scan machine Besides this, X-rays has low ionizing radiations than CT scan COVID-19 reveals some radiological signatures that can be easily detected through chest X-rays For this, radiologists are required to analyze these signatures However, it is a time-consuming and error-prone task Hence, there is a need to automate the analysis of chest X-rays The automatic analysis of chest X-rays can be done through deep learning-based approaches, which may accelerate the analysis time These approaches can train the weights of networks on large datasets as well as fine-tuning the weights of pre-trained networks on small datasets However, these approaches applied to chest X-rays are very limited Hence, the main objective of this paper is to develop an automated deep transfer learning-based approach for detection of COVID-19 infection in chest X-rays by using the extreme version of the Inception (Xception) model Extensive comparative analyses show that the proposed model performs significantly better as compared to the existing models read more read less

Topics:

Transfer of learning (59%)59% related to the paper, Deep learning (57%)57% related to the paper, Computer science (55%)55% related to the paper
215 Citations
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SciSpace is a very innovative solution to the formatting problem and existing providers, such as Mendeley or Word did not really evolve in recent years.

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You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Time taken to format a paper and Compliance with guidelines

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IRBM format uses elsarticle-num citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. Can I write IRBM in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the IRBM guidelines and auto format it.

2. Do you follow the IRBM guidelines?

Yes, the template is compliant with the IRBM guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IRBM?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IRBM citation style.

4. Can I use the IRBM templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for IRBM.

5. Can I use a manuscript in IRBM that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper IRBM that you can download at the end.

6. How long does it usually take you to format my papers in IRBM?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in IRBM.

7. Where can I find the template for the IRBM?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IRBM's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the IRBM's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. IRBM an online tool or is there a desktop version?

SciSpace's IRBM is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like IRBM?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like IRBM?”

11. What is the output that I would get after using IRBM?

After writing your paper autoformatting in IRBM, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IRBM's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IRBM?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IRBM. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IRBM?

The 5 most common citation types in order of usage for IRBM are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the IRBM?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IRBM's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IRBM in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IRBM Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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