Example of IEEE Journal of Biomedical and Health Informatics format
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Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format
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Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format Example of IEEE Journal of Biomedical and Health Informatics format
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This content is only for preview purposes. The original open access content can be found here.
open access Open Access
recommended Recommended

IEEE Journal of Biomedical and Health Informatics — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Computer Science Applications #44 of 693 down down by 11 ranks
Electrical and Electronic Engineering #56 of 693 down down by 15 ranks
Biotechnology #24 of 282 down down by 3 ranks
Health Information Management #4 of 39 up up by 1 rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 981 Published Papers | 10006 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 13/06/2020
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Related Journals

open access Open Access

IEEE

Quality:  
High
CiteRatio: 6.7
SJR: 0.62
SNIP: 1.198
open access Open Access

IEEE

Quality:  
High
CiteRatio: 6.4
SJR: 0.786
SNIP: 2.027
open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 21.6
SJR: 3.216
SNIP: 3.812
open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 7.9
SJR: 0.929
SNIP: 1.478

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.

5.223

24% from 2018

Impact factor for IEEE Journal of Biomedical and Health Informatics from 2016 - 2019
Year Value
2019 5.223
2018 4.217
2017 3.85
2016 3.451
graph view Graph view
table view Table view

10.2

12% from 2019

CiteRatio for IEEE Journal of Biomedical and Health Informatics from 2016 - 2020
Year Value
2020 10.2
2019 9.1
2018 9.2
2017 8.2
2016 6.8
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 24% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 12% 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.

1.293

1% from 2019

SJR for IEEE Journal of Biomedical and Health Informatics from 2016 - 2020
Year Value
2020 1.293
2019 1.306
2018 1.122
2017 0.991
2016 0.94
graph view Graph view
table view Table view

2.448

3% from 2019

SNIP for IEEE Journal of Biomedical and Health Informatics from 2016 - 2020
Year Value
2020 2.448
2019 2.522
2018 2.524
2017 2.193
2016 2.305
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 1% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 3% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
IEEE Journal of Biomedical and Health Informatics

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IEEE

IEEE Journal of Biomedical and Health Informatics

Approved by publishing and review experts on SciSpace, this template is built as per for IEEE Journal of Biomedical and Health Informatics formatting guidelines as mentioned in IEEE author instructions. The current version was created on 13 Jun 2020 and has been used by 953 authors to write and format their manuscripts to this journal.

Engineering

i
Last updated on
13 Jun 2020
i
ISSN
2168-2194
i
Impact Factor
High - 2.388
i
Open Access
No
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
IEEEtran
i
Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker, “Specular andreev reflection in graphene,” Phys. Rev. Lett., vol. 97, no. 6, p.

Top papers written in this journal

Journal Article DOI: 10.1109/JBHI.2012.2234129
A Survey on Ambient-Assisted Living Tools for Older Adults
Parisa Rashidi1, Alex Mihailidis2

Abstract:

In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living t... In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living” (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges. read more read less

Topics:

Independent living (57%)57% related to the paper
1,000 Citations
open accessOpen access Journal Article DOI: 10.1109/JBHI.2017.2767063
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis
Benjamin Shickel1, Patrick J. Tighe1, Azra Bihorac1, Parisa Rashidi1

Abstract:

The past decade has seen an explosion in the amount of digital information stored in electronic health records (EHRs). While primarily designed for archiving patient information and performing administrative healthcare tasks like billing, many researchers have found secondary use of these records for various clinical informat... The past decade has seen an explosion in the amount of digital information stored in electronic health records (EHRs). While primarily designed for archiving patient information and performing administrative healthcare tasks like billing, many researchers have found secondary use of these records for various clinical informatics applications. Over the same period, the machine learning community has seen widespread advances in the field of deep learning. In this review, we survey the current research on applying deep learning to clinical tasks based on EHR data, where we find a variety of deep learning techniques and frameworks being applied to several types of clinical applications including information extraction, representation learning, outcome prediction, phenotyping, and deidentification. We identify several limitations of current research involving topics such as model interpretability, data heterogeneity, and lack of universal benchmarks. We conclude by summarizing the state of the field and identifying avenues of future deep EHR research. read more read less

Topics:

Health informatics (54%)54% related to the paper
View PDF
762 Citations
open accessOpen access Journal Article DOI: 10.1109/JBHI.2017.2731873
Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

Abstract:

Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of a common dataset impedes research when comparing the performance of such alg... Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of a common dataset impedes research when comparing the performance of such algorithms. This paper proposes the use of deep learning approaches for breast ultrasound lesion detection and investigates three different methods: a Patch-based LeNet, a U-Net, and a transfer learning approach with a pretrained FCN-AlexNet. Their performance is compared against four state-of-the-art lesion detection algorithms (i.e., Radial Gradient Index, Multifractal Filtering, Rule-based Region Ranking, and Deformable Part Models). In addition, this paper compares and contrasts two conventional ultrasound image datasets acquired from two different ultrasound systems. Dataset A comprises 306 (60 malignant and 246 benign) images and Dataset B comprises 163 (53 malignant and 110 benign) images. To overcome the lack of public datasets in this domain, Dataset B will be made available for research purposes. The results demonstrate an overall improvement by the deep learning approaches when assessed on both datasets in terms of True Positive Fraction, False Positives per image, and F-measure. read more read less

Topics:

Breast ultrasound (56%)56% related to the paper, Deep learning (50%)50% related to the paper
View PDF
564 Citations
open accessOpen access Journal Article DOI: 10.1109/JBHI.2015.2450362
Big Data for Health
Javier Andreu-Perez1, Carmen C. Y. Poon2, Robert Merrifield1, Stephen T. C. Wong3, Guang-Zhong Yang1

Abstract:

This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of p... This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled. read more read less

Topics:

Health informatics (66%)66% related to the paper, Health Administration Informatics (66%)66% related to the paper, Imaging informatics (62%)62% related to the paper, Engineering informatics (60%)60% related to the paper, Translational bioinformatics (60%)60% related to the paper
505 Citations
open accessOpen access Journal Article DOI: 10.1109/JBHI.2017.2688239
DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices
Stamos Katsigiannis1, Naeem Ramzan1

Abstract:

In this paper, we present DREAMER, a multimodal database consisting of electroencephalogram (EEG) and electrocardiogram (ECG) signals recorded during affect elicitation by means of audio-visual stimuli. Signals from 23 participants were recorded along with the participants self-assessment of their affective state after each s... In this paper, we present DREAMER, a multimodal database consisting of electroencephalogram (EEG) and electrocardiogram (ECG) signals recorded during affect elicitation by means of audio-visual stimuli. Signals from 23 participants were recorded along with the participants self-assessment of their affective state after each stimuli, in terms of valence, arousal, and dominance. All the signals were captured using portable, wearable, wireless, low-cost, and off-the-shelf equipment that has the potential to allow the use of affective computing methods in everyday applications. A baseline for participant-wise affect recognition using EEG and ECG-based features, as well as their fusion, was established through supervised classification experiments using support vector machines (SVMs). The self-assessment of the participants was evaluated through comparison with the self-assessments from another study using the same audio-visual stimuli. Classification results for valence, arousal, and dominance of the proposed database are comparable to the ones achieved for other databases that use nonportable, expensive, medical grade devices. These results indicate the prospects of using low-cost devices for affect recognition applications. The proposed database will be made publicly available in order to allow researchers to achieve a more thorough evaluation of the suitability of these capturing devices for affect recognition applications. read more read less

Topics:

Affective computing (53%)53% related to the paper
View PDF
493 Citations
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IEEE Journal of Biomedical and Health Informatics format uses IEEEtran citation style.

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

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Frequently asked questions

1. Can I write IEEE Journal of Biomedical and Health Informatics in LaTeX?

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

2. Do you follow the IEEE Journal of Biomedical and Health Informatics guidelines?

Yes, the template is compliant with the IEEE Journal of Biomedical and Health Informatics 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 IEEE Journal of Biomedical and Health Informatics?

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 IEEE Journal of Biomedical and Health Informatics citation style.

4. Can I use the IEEE Journal of Biomedical and Health Informatics 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 IEEE Journal of Biomedical and Health Informatics.

5. Can I use a manuscript in IEEE Journal of Biomedical and Health Informatics 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 IEEE Journal of Biomedical and Health Informatics that you can download at the end.

6. How long does it usually take you to format my papers in IEEE Journal of Biomedical and Health Informatics?

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

7. Where can I find the template for the IEEE Journal of Biomedical and Health Informatics?

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 IEEE Journal of Biomedical and Health Informatics'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 IEEE Journal of Biomedical and Health Informatics'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. IEEE Journal of Biomedical and Health Informatics an online tool or is there a desktop version?

SciSpace's IEEE Journal of Biomedical and Health Informatics 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 IEEE Journal of Biomedical and Health Informatics?

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 IEEE Journal of Biomedical and Health Informatics?”

11. What is the output that I would get after using IEEE Journal of Biomedical and Health Informatics?

After writing your paper autoformatting in IEEE Journal of Biomedical and Health Informatics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IEEE Journal of Biomedical and Health Informatics'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 IEEE Journal of Biomedical and Health Informatics?

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 IEEE Journal of Biomedical and Health Informatics. 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 IEEE Journal of Biomedical and Health Informatics?

The 5 most common citation types in order of usage for IEEE Journal of Biomedical and Health Informatics 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 IEEE Journal of Biomedical and Health Informatics?

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 IEEE Journal of Biomedical and Health Informatics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IEEE Journal of Biomedical and Health Informatics 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 IEEE Journal of Biomedical and Health Informatics 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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