"Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆." - Information and Links:

Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆. - Info and Reading Options

"Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆." and the language of the book is English.


“Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” Metadata:

  • Title: ➤  Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.
  • Authors:
  • Language: English

Edition Identifiers:

  • Internet Archive ID: pubmed-PMC3814947

AI-generated Review of “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.”:


"Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆." Description:

The Internet Archive:

This article is from <a href="//archive.org/search.php?query=journaltitle%3A%28NeuroImage%20:%20Clinical%29" rel="ugc nofollow">NeuroImage : Clinical</a>, <a href="//archive.org/search.php?query=journaltitle%3A%28NeuroImage%20:%20Clinical%29%20AND%20volume%3A%283%29" rel="ugc nofollow">volume 3</a>.<h2>Abstract</h2>Standard univariate analyses of brain imaging data have revealed a host of structural and functional brain alterations in schizophrenia. However, these analyses typically involve examining each voxel separately and making inferences at group-level, thus limiting clinical translation of their findings. Taking into account the fact that brain alterations in schizophrenia expand over a widely distributed network of brain regions, univariate analysis methods may not be the most suited choice for imaging data analysis. To address these limitations, the neuroimaging community has turned to machine learning methods both because of their ability to examine voxels jointly and their potential for making inferences at a single-subject level. This article provides a critical overview of the current and foreseeable applications of machine learning, in identifying imaging-based biomarkers that could be used for the diagnosis, early detection and treatment response of schizophrenia, and could, thus, be of high clinical relevance. We discuss promising future research directions and the main difficulties facing machine learning researchers as far as their potential translation into clinical practice is concerned.

Read “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.”:

Read “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” by choosing from the options below.

Available Downloads for “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.”:

"Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆." is available for download from The Internet Archive in "texts" format, the size of the file-s is: 11.52 Mbs, and the file-s went public at Tue Oct 28 2014.

Legal and Safety Notes

Copyright Disclaimer and Liability Limitation:

A. Automated Content Display
The creation of this page is fully automated. All data, including text, images, and links, is displayed exactly as received from its original source, without any modification, alteration, or verification. We do not claim ownership of, nor assume any responsibility for, the accuracy or legality of this content.

B. Liability Disclaimer for External Content
The files provided below are solely the responsibility of their respective originators. We disclaim any and all liability, whether direct or indirect, for the content, accuracy, legality, or any other aspect of these files. By using this website, you acknowledge that we have no control over, nor endorse, the content hosted by external sources.

C. Inquiries and Disputes
For any inquiries, concerns, or issues related to the content displayed, including potential copyright claims, please contact the original source or provider of the files directly. We are not responsible for resolving any content-related disputes or claims of intellectual property infringement.

D. No Copyright Ownership
We do not claim ownership of any intellectual property contained in the files or data displayed on this website. All copyrights, trademarks, and other intellectual property rights remain the sole property of their respective owners. If you believe that content displayed on this website infringes upon your intellectual property rights, please contact the original content provider directly.

E. Fair Use Notice
Some content displayed on this website may fall under the "fair use" provisions of copyright law for purposes such as commentary, criticism, news reporting, research, or educational purposes. If you believe any content violates fair use guidelines, please reach out directly to the original source of the content for resolution.

Virus Scanning for Your Peace of Mind:

The files provided below have already been scanned for viruses by their original source. However, if you’d like to double-check before downloading, you can easily scan them yourself using the following steps:

How to scan a direct download link for viruses:

  • 1- Copy the direct link to the file you want to download (don’t open it yet).
    • (a free online tool) and paste the direct link into the provided field to start the scan.
  • 2- Visit VirusTotal (a free online tool) and paste the direct link into the provided field to start the scan.
  • 3- VirusTotal will scan the file using multiple antivirus vendors to detect any potential threats.
  • 4- Once the scan confirms the file is safe, you can proceed to download it with confidence and enjoy your content.

Available Downloads

  • Source: Internet Archive
  • Internet Archive Link: Archive.org page
  • All Files are Available: Yes
  • Number of Files: 14
  • Number of Available Files: 14
  • Added Date: 2014-10-28 09:31:48
  • Scanner: Internet Archive Python library 0.7.5
  • PPI (Pixels Per Inch): 300
  • OCR: ABBYY FineReader 9.0

Available Files:

1- Text PDF

  • File origin: original
  • File Format: Text PDF
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003.pdf
  • Direct Link: Click here

2- Item Tile

  • File origin: original
  • File Format: Item Tile
  • File Size: 0.00 Mbs
  • File Name: __ia_thumb.jpg
  • Direct Link: Click here

3- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC3814947_files.xml
  • Direct Link: Click here

4- JSON

  • File origin: original
  • File Format: JSON
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC3814947_medline.json
  • Direct Link: Click here

5- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC3814947_meta.sqlite
  • Direct Link: Click here

6- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC3814947_meta.xml
  • Direct Link: Click here

7- DjVu

  • File origin: derivative
  • File Format: DjVu
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003.djvu
  • Direct Link: Click here

8- Animated GIF

  • File origin: derivative
  • File Format: Animated GIF
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003.gif
  • Direct Link: Click here

9- Abbyy GZ

  • File origin: derivative
  • File Format: Abbyy GZ
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003_abbyy.gz
  • Direct Link: Click here

10- DjVuTXT

  • File origin: derivative
  • File Format: DjVuTXT
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003_djvu.txt
  • Direct Link: Click here

11- Djvu XML

  • File origin: derivative
  • File Format: Djvu XML
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003_djvu.xml
  • Direct Link: Click here

12- Single Page Processed JP2 ZIP

  • File origin: derivative
  • File Format: Single Page Processed JP2 ZIP
  • File Size: 0.01 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003_jp2.zip
  • Direct Link: Click here

13- Scandata

  • File origin: derivative
  • File Format: Scandata
  • File Size: 0.00 Mbs
  • File Name: PMC3814947-j.nicl.2013.09.003_scandata.xml
  • Direct Link: Click here

14- Archive BitTorrent

  • File origin: metadata
  • File Format: Archive BitTorrent
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC3814947_archive.torrent
  • Direct Link: Click here

Search for “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” in Libraries Near You:

Read or borrow “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” from your local library.

Buy “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” online:

Shop for “Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆.” on popular online marketplaces.



Find "Towards The Identification Of Imaging Biomarkers In Schizophrenia, Using Multivariate Pattern Classification At A Single-subject Level☆." in Wikipdedia