Engineers Garage

  • Electronic Projects & Tutorials
    • Electronic Projects
      • Arduino Projects
      • AVR
      • Raspberry pi
      • ESP8266
      • BeagleBone
      • 8051 Microcontroller
      • ARM
      • PIC Microcontroller
      • STM32
    • Tutorials
      • Audio Electronics
      • Battery Management
      • Brainwave
      • Electric Vehicles
      • EMI/EMC/RFI
      • Hardware Filters
      • IoT tutorials
      • Power Tutorials
      • Python
      • Sensors
      • USB
      • VHDL
    • Circuit Design
    • Project Videos
    • Components
  • Articles
    • Tech Articles
    • Insight
    • Invention Stories
    • How to
    • What Is
  • News
    • Electronic Product News
    • Business News
    • Company/Start-up News
    • DIY Reviews
    • Guest Post
  • Forums
    • EDABoard.com
    • Electro-Tech-Online
    • EG Forum Archive
  • DigiKey Store
    • Cables, Wires
    • Connectors, Interconnect
    • Discrete
    • Electromechanical
    • Embedded Computers
    • Enclosures, Hardware, Office
    • Integrated Circuits (ICs)
    • Isolators
    • LED/Optoelectronics
    • Passive
    • Power, Circuit Protection
    • Programmers
    • RF, Wireless
    • Semiconductors
    • Sensors, Transducers
    • Test Products
    • Tools
  • Learn
    • eBooks/Tech Tips
    • Design Guides
    • Learning Center
    • Tech Toolboxes
    • Webinars & Digital Events
  • Resources
    • Digital Issues
    • EE Training Days
    • LEAP Awards
    • Podcasts
    • Webinars / Digital Events
    • White Papers
    • Engineering Diversity & Inclusion
    • DesignFast
  • Guest Post Guidelines
  • Advertise
  • Subscribe

Psychologists Use Machine Learning to Help Identify Depression

By Parul Gupta March 28, 2017

The scientist is using the Stampede supercomputer at the Texas Advanced Computing Centre to train a machine learning algorithm that can recognize common issues among hundreds of patients employing Magnetic Resonance Imaging brain scans, genomics and other vital factors, to offer precise predictions of risk for those with anxiety and depression.

Scientists have long studied mental issues by analysing the relationship between brain structure and function in neuroimaging data. “One problem with that work is that it is mainly descriptive. The brain networks may appear to differ between two groups, but it does not inform us about patterns that actually identify which group you would fall into,” says Schnyer. “We are searching for diagnostic measures that are predictive for results such as vulnerability to dementia and depression.”

The machine that Schnyer and his group tested is known as Support Vector Machine Learning. The scientists offered a set of training examples each considered belonging to either healthy people for those who have been identified with depression. Schnyer and his group named the machine as labelled features in their data that were meaningful, and such examples were employed to train the system.

In the study, Schnyer analysed brain information from 52 treatment seeking participants with depression, and 45 healthy control participants. For a comparison, they matched a subset of depressed participants with individuals based on gender and age. “We feed in entire brain data or a subset and predict ailment classifications or any potential behavioural measure like measures of negative information bias,” he confirms. The research disclosed that DTI-derived fractional anisotropy maps can precisely classify vulnerable or depressed individuals versus healthy controls. It also revealed that predictive data is distributed across brain networks rather than being exceedingly localized.

machine learning to help diagnose depression

The results obtained are promising, but still not clear enough to be employed as a clinical metric. But, Schnyer believes that by supplementing more data related to not just MRI scans but also form genomics and other classifiers, the system can perform much better.
“One of the primary benefits of this machine learning, compared to conventional approaches is that machine learning should enhance the likelihood that what we observe in the study will apply to novel and independent datasets. So, it must generalize to novel data,” says Beevers.

Schnyer and Beevers will expand their research to include data from numerous hundred volunteers from the Austin group who have been identified with depression, anxiety or a related situation Stampede 2 – TACC’s newest supercomputer which will come online later in 2017 and will be twice as powerful as the present system, will offer the enhanced computer processing power needed to include more data and achieve greater accuracy.


Filed Under: News
Tagged With: Research
 

Next Article

← Previous Article
Next Article →

Questions related to this article?
👉Ask and discuss on Electro-Tech-Online.com and EDAboard.com forums.



Tell Us What You Think!! Cancel reply

You must be logged in to post a comment.

EE TECH TOOLBOX

“ee
Tech Toolbox: 5G Technology
This Tech Toolbox covers the basics of 5G technology plus a story about how engineers designed and built a prototype DSL router mostly from old cellphone parts. Download this first 5G/wired/wireless communications Tech Toolbox to learn more!

EE Learning Center

EE Learning Center
“engineers
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, tools and strategies for EE professionals.

HAVE A QUESTION?

Have a technical question about an article or other engineering questions? Check out our engineering forums EDABoard.com and Electro-Tech-Online.com where you can get those questions asked and answered by your peers!


RSS EDABOARD.com Discussions

  • Sendust vs Ferrite for SMPS
  • connector model question
  • value of feedback resistance in self biased inverter
  • Industrial Relay Board Design for Motorcycle Use
  • sim7090g

RSS Electro-Tech-Online.com Discussions

  • using a RTC in SF basic
  • It's Amazing What A Buck And A Quarter....
  • Microinverters and storeage batteries?
  • ac current limiting
  • More fun with ws2812 this time XC8 and CLC

Featured – LoRa/LoRaWan Series

  • What is the LoRaWAN network and how does it work?
  • Understanding LoRa architecture: nodes, gateways, and servers
  • Revolutionizing RF: LoRa applications and advantages
  • How to build a LoRa gateway using Raspberry Pi
  • How LoRa enables long-range communication
  • How communication works between two LoRa end-node devices

Recent Articles

  • Infineon launches 3D magnetic sensors with ±50 mT to ±160 mT measurement ranges
  • Nexperia adds 1200 V 20 A silicon carbide Schottky diodes to power portfolio
  • EPC introduces 15 ARMS per phase motor drive in 32 mm diameter form factor
  • Non-contact angle sensors deliver +0.3% linearity across full measurement range
  • TDK introduces RGF board-mount EMI filters for high-current power supply applications

EE ENGINEERING TRAINING DAYS

engineering

Submit a Guest Post

submit a guest post
Engineers Garage
  • Analog IC TIps
  • Connector Tips
  • Battery Power Tips
  • DesignFast
  • EDABoard Forums
  • EE World Online
  • Electro-Tech-Online Forums
  • EV Engineering
  • Microcontroller Tips
  • Power Electronic Tips
  • Sensor Tips
  • Test and Measurement Tips
  • 5G Technology World
  • Subscribe to our newsletter
  • About Us
  • Contact Us
  • Advertise

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy

Search Engineers Garage

  • Electronic Projects & Tutorials
    • Electronic Projects
      • Arduino Projects
      • AVR
      • Raspberry pi
      • ESP8266
      • BeagleBone
      • 8051 Microcontroller
      • ARM
      • PIC Microcontroller
      • STM32
    • Tutorials
      • Audio Electronics
      • Battery Management
      • Brainwave
      • Electric Vehicles
      • EMI/EMC/RFI
      • Hardware Filters
      • IoT tutorials
      • Power Tutorials
      • Python
      • Sensors
      • USB
      • VHDL
    • Circuit Design
    • Project Videos
    • Components
  • Articles
    • Tech Articles
    • Insight
    • Invention Stories
    • How to
    • What Is
  • News
    • Electronic Product News
    • Business News
    • Company/Start-up News
    • DIY Reviews
    • Guest Post
  • Forums
    • EDABoard.com
    • Electro-Tech-Online
    • EG Forum Archive
  • DigiKey Store
    • Cables, Wires
    • Connectors, Interconnect
    • Discrete
    • Electromechanical
    • Embedded Computers
    • Enclosures, Hardware, Office
    • Integrated Circuits (ICs)
    • Isolators
    • LED/Optoelectronics
    • Passive
    • Power, Circuit Protection
    • Programmers
    • RF, Wireless
    • Semiconductors
    • Sensors, Transducers
    • Test Products
    • Tools
  • Learn
    • eBooks/Tech Tips
    • Design Guides
    • Learning Center
    • Tech Toolboxes
    • Webinars & Digital Events
  • Resources
    • Digital Issues
    • EE Training Days
    • LEAP Awards
    • Podcasts
    • Webinars / Digital Events
    • White Papers
    • Engineering Diversity & Inclusion
    • DesignFast
  • Guest Post Guidelines
  • Advertise
  • Subscribe