Example of Nature Biomedical Engineering format
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Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format
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Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format Example of Nature Biomedical Engineering format
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Nature Biomedical Engineering — Template for authors

Publisher: Nature
Categories Rank Trend in last 3 yrs
Computer Science Applications #2 of 693 up up by 143 ranks
Medicine (miscellaneous) #2 of 238 up up by 65 ranks
Biotechnology #3 of 282 up up by 81 ranks
Biomedical Engineering #4 of 229 up up by 59 ranks
Bioengineering #4 of 148 up up by 53 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 378 Published Papers | 10597 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 25/06/2020
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Related Journals

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Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

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

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.

28.0

57% from 2019

CiteRatio for Nature Biomedical Engineering from 2016 - 2020
Year Value
2020 28.0
2019 17.8
2018 10.2
2017 4.0
graph view Graph view
table view Table view

5.961

1% from 2019

SJR for Nature Biomedical Engineering from 2018 - 2020
Year Value
2020 5.961
2019 5.887
2018 4.974
graph view Graph view
table view Table view

3.528

9% from 2019

SNIP for Nature Biomedical Engineering from 2018 - 2020
Year Value
2020 3.528
2019 3.862
2018 3.503
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 57% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased 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 9% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Nature Biomedical Engineering

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Nature

Nature Biomedical Engineering

Straddling the life sciences, the physical sciences and engineering, the journal publishes biological, medical and engineering advances technological, translational, methodological or fundamental that can directly inspire or lead to improvements in human health. ... Read More

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Last updated on
25 Jun 2020
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ISSN
2157-846X
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Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
Yes
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Citation Type
Numbered (Superscripted)
25
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Bibliography Example
Beenakker, C. W. J. Specular andreev reflection in graphene. Phys. Rev. Lett. 97, 067007 (2006). URL 10.1103/PhysRevLett.97.067007.

Top papers written in this journal

Journal Article DOI: 10.1038/S41551-016-0010
Near-infrared fluorophores for biomedical imaging
Guosong Hong1, Guosong Hong2, Alexander L. Antaris1, Hongjie Dai1

Abstract:

This Review covers recent progress on near-infrared fluorescence imaging for preclinical animal studies and clinical diagnostics and interventions.
1,774 Citations
Journal Article DOI: 10.1038/S41551-018-0305-Z
Artificial Intelligence in Healthcare
Kun-Hsing Yu1, Andrew L. Beam1, Isaac S. Kohane1, Isaac S. Kohane2

Abstract:

Artificial intelligence (AI) is gradually changing medical practice. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding into areas that were previously thought to be only the province of human experts. In this Review Article, we outline recent break... Artificial intelligence (AI) is gradually changing medical practice. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding into areas that were previously thought to be only the province of human experts. In this Review Article, we outline recent breakthroughs in AI technologies and their biomedical applications, identify the challenges for further progress in medical AI systems, and summarize the economic, legal and social implications of AI in healthcare. read more read less

Topics:

Applications of artificial intelligence (68%)68% related to the paper
1,315 Citations
open accessOpen access Journal Article DOI: 10.1038/S41551-018-0195-0
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning

Abstract:

Traditionally, medical discoveries are made by observing associations, making hypotheses from them and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can often be difficult because of the wide variety of features, patterns, colours, values an... Traditionally, medical discoveries are made by observing associations, making hypotheses from them and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can often be difficult because of the wide variety of features, patterns, colours, values and shapes that are present in real data. Here, we show that deep learning can extract new knowledge from retinal fundus images. Using deep-learning models trained on data from 284,335 patients and validated on two independent datasets of 12,026 and 999 patients, we predicted cardiovascular risk factors not previously thought to be present or quantifiable in retinal images, such as age (mean absolute error within 3.26 years), gender (area under the receiver operating characteristic curve (AUC) = 0.97), smoking status (AUC = 0.71), systolic blood pressure (mean absolute error within 11.23 mmHg) and major adverse cardiac events (AUC = 0.70). We also show that the trained deep-learning models used anatomical features, such as the optic disc or blood vessels, to generate each prediction. read more read less

Topics:

Receiver operating characteristic (51%)51% related to the paper
1,038 Citations
open accessOpen access Journal Article DOI: 10.1038/S41551-018-0304-0
Explainable Machine-Learning Predictions for the Prevention of Hypoxaemia During Surgery

Abstract:

Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time during general anaesthesia, predicts the risk of hypoxemia and provides explanat... Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time during general anaesthesia, predicts the risk of hypoxemia and provides explanations of the risk factors. The system, which was trained on minute-by-minute data from the electronic medical records of over fifty thousand surgeries, improved the performance of anaesthesiologists when providing interpretable hypoxemia risks and contributing factors. The explanations for the predictions are broadly consistent with the literature and with prior knowledge from anaesthesiologists. Our results suggest that if anaesthesiologists currently anticipate 15% of hypoxemia events, with this system's assistance they would anticipate 30% of them, a large portion of which may benefit from early intervention because they are associated with modifiable factors. The system can help improve the clinical understanding of hypoxemia risk during anaesthesia care by providing general insights into the exact changes in risk induced by certain patient or procedure characteristics. read more read less

Topics:

Hypoxemia (51%)51% related to the paper
View PDF
956 Citations
open accessOpen access Journal Article DOI: 10.1038/S41551-018-0236-8
TLR7/8-agonist-loaded nanoparticles promote the polarization of tumour-associated macrophages to enhance cancer immunotherapy.

Abstract:

Tumour-associated macrophages are abundant in many cancers, and often display an immune-suppressive M2-like phenotype that fosters tumour growth and promotes resistance to therapy. Yet, macrophages are highly plastic and can also acquire an anti-tumorigenic M1-like phenotype. Here, we show that R848, an agonist of the toll-li... Tumour-associated macrophages are abundant in many cancers, and often display an immune-suppressive M2-like phenotype that fosters tumour growth and promotes resistance to therapy. Yet, macrophages are highly plastic and can also acquire an anti-tumorigenic M1-like phenotype. Here, we show that R848, an agonist of the toll-like receptors TLR7 and TLR8 identified in a morphometric-based screen, is a potent driver of the M1 phenotype in vitro and that R848-loaded β-cyclodextrin nanoparticles (CDNP-R848) lead to efficient drug delivery to tumour-associated macrophages in vivo. As a monotherapy, the administration of CDNP-R848 in multiple tumour models in mice altered the functional orientation of the tumour immune microenvironment towards an M1 phenotype, leading to controlled tumour growth and protecting the animals against tumour rechallenge. When used in combination with the immune checkpoint inhibitor anti-PD-1, we observed improved immunotherapy response rates, including in a tumour model resistant to anti-PD-1 therapy alone. Our findings demonstrate the ability of rationally engineered drug-nanoparticle combinations to efficiently modulate tumour-associated macrophages for cancer immunotherapy. read more read less

Topics:

Immunotherapy (56%)56% related to the paper, Cancer immunotherapy (53%)53% related to the paper
View PDF
601 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.

- Andreas Frutiger, Researcher, ETH Zurich, Institute for Biomedical Engineering

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With SciSpace, you do not need a word template for Nature Biomedical Engineering.

It automatically formats your research paper to Nature formatting guidelines and citation style.

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

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Frequently asked questions

1. Can I write Nature Biomedical Engineering in LaTeX?

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

2. Do you follow the Nature Biomedical Engineering guidelines?

Yes, the template is compliant with the Nature Biomedical Engineering 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 Nature Biomedical Engineering?

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 Nature Biomedical Engineering citation style.

4. Can I use the Nature Biomedical Engineering 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 Nature Biomedical Engineering.

5. Can I use a manuscript in Nature Biomedical Engineering 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 Nature Biomedical Engineering that you can download at the end.

6. How long does it usually take you to format my papers in Nature Biomedical Engineering?

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

7. Where can I find the template for the Nature Biomedical Engineering?

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 Nature Biomedical Engineering'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 Nature Biomedical Engineering'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. Nature Biomedical Engineering an online tool or is there a desktop version?

SciSpace's Nature Biomedical Engineering 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 Nature Biomedical Engineering?

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 Nature Biomedical Engineering?”

11. What is the output that I would get after using Nature Biomedical Engineering?

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

12. Is Nature Biomedical Engineering'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 Nature Biomedical Engineering?

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 Nature Biomedical Engineering. 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 Nature Biomedical Engineering?

The 5 most common citation types in order of usage for Nature Biomedical Engineering 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 Nature Biomedical Engineering?

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 Nature Biomedical Engineering's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Nature Biomedical Engineering 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 Nature Biomedical Engineering 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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