Example of Journal of Healthcare Engineering format
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Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format
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Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering format Example of Journal of Healthcare Engineering 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

Journal of Healthcare Engineering — Template for authors

Publisher: Hindawi
Categories Rank Trend in last 3 yrs
Surgery #56 of 422 up up by 230 ranks
Health Informatics #26 of 95 up up by 28 ranks
Biotechnology #101 of 282 up up by 95 ranks
Biomedical Engineering #90 of 229 up up by 77 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 643 Published Papers | 2945 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 02/06/2020
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Related Journals

open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 7.7
SJR: 1.053
SNIP: 1.746
open access Open Access

American Chemical Society

Quality:  
High
CiteRatio: 8.1
SJR: 1.279
SNIP: 0.942
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recommended Recommended

IOP Publishing

Quality:  
High
CiteRatio: 13.9
SJR: 2.328
SNIP: 1.621

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.

1.803

39% from 2018

Impact factor for Journal of Healthcare Engineering from 2016 - 2019
Year Value
2019 1.803
2018 1.295
2017 1.261
2016 0.965
graph view Graph view
table view Table view

4.6

77% from 2019

CiteRatio for Journal of Healthcare Engineering from 2016 - 2020
Year Value
2020 4.6
2019 2.6
2018 1.2
2017 0.8
2016 2.5
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 39% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 77% 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.

0.509

21% from 2019

SJR for Journal of Healthcare Engineering from 2016 - 2020
Year Value
2020 0.509
2019 0.42
2018 0.28
2017 0.28
2016 0.278
graph view Graph view
table view Table view

1.422

35% from 2019

SNIP for Journal of Healthcare Engineering from 2016 - 2020
Year Value
2020 1.422
2019 1.052
2018 0.792
2017 0.535
2016 0.493
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 35% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Healthcare Engineering

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Hindawi

Journal of Healthcare Engineering

The Journal of Healthcare Engineering is a peer-reviewed, Open Access journal publishing fundamental and applied research on all aspects of engineering involved in healthcare delivery processes and systems. It provides a vehicle for the exchange of advanced knowledge, emerging...... Read More

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Last updated on
02 Jun 2020
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ISSN
2040-2295
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Impact Factor
Medium - 0.96
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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
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Citation Type
Numbered
[25]
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Bibliography Example
C. W. J. Beenakker. “Specular andreev reflection in graphene”. Phys. Rev. Lett., vol. 97, no. 6, 067007, 2006.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1155/2019/4180949
An Efficient Deep Learning Approach to Pneumonia Classification in Healthcare.
Okeke Stephen1, Mangal Sain1, Uchenna Joseph Maduh2, Do-Un Jeong1

Abstract:

This study proposes a convolutional neural network model trained from scratch to classify and detect the presence of pneumonia from a collection of chest X-ray image samples. Unlike other methods that rely solely on transfer learning approaches or traditional handcrafted techniques to achieve a remarkable classification perfo... This study proposes a convolutional neural network model trained from scratch to classify and detect the presence of pneumonia from a collection of chest X-ray image samples. Unlike other methods that rely solely on transfer learning approaches or traditional handcrafted techniques to achieve a remarkable classification performance, we constructed a convolutional neural network model from scratch to extract features from a given chest X-ray image and classify it to determine if a person is infected with pneumonia. This model could help mitigate the reliability and interpretability challenges often faced when dealing with medical imagery. Unlike other deep learning classification tasks with sufficient image repository, it is difficult to obtain a large amount of pneumonia dataset for this classification task; therefore, we deployed several data augmentation algorithms to improve the validation and classification accuracy of the CNN model and achieved remarkable validation accuracy. read more read less

Topics:

Deep learning (57%)57% related to the paper, Convolutional neural network (54%)54% related to the paper, Interpretability (50%)50% related to the paper
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358 Citations
open accessOpen access Journal Article DOI: 10.1155/2017/4037190
A benchmark for endoluminal scene segmentation of colonoscopy images

Abstract:

Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss rate and the inability to ... Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss rate and the inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing decision support systems (DSS) aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endoluminal scene, targeting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCNs). We perform a comparative study to show that FCNs significantly outperform, without any further postprocessing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization. read more read less

Topics:

Image segmentation (56%)56% related to the paper, Segmentation (51%)51% related to the paper
View PDF
310 Citations
open accessOpen access Journal Article DOI: 10.1155/2017/8314740
Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.
QingZeng Song, Lei Zhao, XingKe Luo, XueChen Dou

Abstract:

Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depends on the experience of doctors, which may ignore some patients and cause so... Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depends on the experience of doctors, which may ignore some patients and cause some problems. Deep learning has been proved as a popular and powerful method in many medical imaging diagnosis areas. In this paper, three types of deep neural networks (e.g., CNN, DNN, and SAE) are designed for lung cancer calcification. Those networks are applied to the CT image classification task with some modification for the benign and malignant lung nodules. Those networks were evaluated on the LIDC-IDRI database. The experimental results show that the CNN network archived the best performance with an accuracy of 84.15%, sensitivity of 83.96%, and specificity of 84.32%, which has the best result among the three networks. read more read less

Topics:

Lung cancer (53%)53% related to the paper
View PDF
304 Citations
open accessOpen access Journal Article DOI: 10.1155/2019/5340616
The Role of 3D Printing in Medical Applications: A State of the Art
Anna Aimar, Augusto Palermo, Bernardo Innocenti1

Abstract:

Three-dimensional (3D) printing refers to a number of manufacturing technologies that generate a physical model from digital information. Medical 3D printing was once an ambitious pipe dream. However, time and investment made it real. Nowadays, the 3D printing technology represents a big opportunity to help pharmaceutical and... Three-dimensional (3D) printing refers to a number of manufacturing technologies that generate a physical model from digital information. Medical 3D printing was once an ambitious pipe dream. However, time and investment made it real. Nowadays, the 3D printing technology represents a big opportunity to help pharmaceutical and medical companies to create more specific drugs, enabling a rapid production of medical implants, and changing the way that doctors and surgeons plan procedures. Patient-specific 3D-printed anatomical models are becoming increasingly useful tools in today's practice of precision medicine and for personalized treatments. In the future, 3D-printed implantable organs will probably be available, reducing the waiting lists and increasing the number of lives saved. Additive manufacturing for healthcare is still very much a work in progress, but it is already applied in many different ways in medical field that, already reeling under immense pressure with regards to optimal performance and reduced costs, will stand to gain unprecedented benefits from this good-as-gold technology. The goal of this analysis is to demonstrate by a deep research of the 3D-printing applications in medical field the usefulness and drawbacks and how powerful technology it is. read more read less
View PDF
297 Citations
open accessOpen access Journal Article DOI: 10.1155/2017/3090343
A Review on Human Activity Recognition Using Vision-Based Method
Shugang Zhang1, Zhiqiang Wei1, Jie Nie2, Lei Huang1, Shuang Wang1, Zhen Li1

Abstract:

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the ad... Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research. read more read less

Topics:

Activity recognition (55%)55% related to the paper, Taxonomy (general) (51%)51% related to the paper
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239 Citations
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Frequently asked questions

1. Can I write Journal of Healthcare 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 Journal of Healthcare Engineering guidelines and auto format it.

2. Do you follow the Journal of Healthcare Engineering guidelines?

Yes, the template is compliant with the Journal of Healthcare 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 Journal of Healthcare 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 Journal of Healthcare Engineering citation style.

4. Can I use the Journal of Healthcare 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 Journal of Healthcare Engineering.

5. Can I use a manuscript in Journal of Healthcare 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 Journal of Healthcare Engineering that you can download at the end.

6. How long does it usually take you to format my papers in Journal of Healthcare 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 Journal of Healthcare Engineering.

7. Where can I find the template for the Journal of Healthcare 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 Journal of Healthcare 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 Journal of Healthcare 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. Journal of Healthcare Engineering an online tool or is there a desktop version?

SciSpace's Journal of Healthcare 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 Journal of Healthcare 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 Journal of Healthcare Engineering?”

11. What is the output that I would get after using Journal of Healthcare Engineering?

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

12. Is Journal of Healthcare 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 Journal of Healthcare 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 Journal of Healthcare 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 Journal of Healthcare Engineering?

The 5 most common citation types in order of usage for Journal of Healthcare 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 Journal of Healthcare 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 Journal of Healthcare Engineering's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Journal of Healthcare 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 Journal of Healthcare 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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