Generic filters
Filter by input type
Select all
News
Pages
Events
Filter by category
Select all
AI ANALYTICS
Mobile Apps and Internet of Things
Advancement of science
big data
Connected communities
Coronavirus
Courses and training
DIAGNOSIS
Initial Editorial
Editorials
A world in the cloud
Events
Infographics
Artificial Intelligence and Science
IoT Apps
News
Digital platforms
Social networks
Review of scientific publications
Course Summary
Synopsis of essay
Overview of reference frames
Synopsis of recent publications
Use of Digital Platforms
Generic filters
Filter by input type
Select all
News
Pages
Events
Filter by category
Select all
AI ANALYTICS
Mobile Apps and Internet of Things
Advancement of science
big data
Connected communities
Coronavirus
Courses and training
DIAGNOSIS
Initial Editorial
Editorials
A world in the cloud
Events
Infographics
Artificial Intelligence and Science
IoT Apps
News
Digital platforms
Social networks
Review of scientific publications
Course Summary
Synopsis of essay
Overview of reference frames
Synopsis of recent publications
Use of Digital Platforms
Research shows the effectiveness of Artificial Intelligence to predict psychological distress

BMJ Open published a cross-sectional study comparing the use of Artificial Intelligence (AI) and psychiatric studies to measure psychological distress among workers.

Psychological discomfort is a problem that, as explained by the authors of the study carried out in Tsukuba Science City, in Japan, must be addressed in the field of occupational health. Their study aimed to use AI to predict psychological distress among workers. In this, sociodemographic, lifestyle and sleep factors were taken into account, not subjective information such as mood and emotions. The results of the psychiatrists were compared with the AI models.

The study analyzed data from 7,251 workers. The AI model based on a neural network, calculated the precision, sensitivity and specificity. Furthermore, the six participating psychiatrists used the same data as the AI model for the prediction of psychological distress.

"An artificial intelligence model was created to predict psychological distress and then the results were compared in terms of accuracy with predictions made by psychiatrists," the authors explain.

The results for the IA model accuracies in predicting moderate psychological distress were 65.2% and the psychiatrists' accuracies were 64.4%, so there were no significant differences. However, the accuracy of the AI model to predict severe psychological distress was 89.9%, against 85.5% for psychiatrists, so the AI in this case had a significantly higher accuracy.

“A machine learning model was successfully developed to assess workers with depressed mood. The explanatory variables used for the predictions did not ask directly about mood. Therefore, this newly developed model appears to be able to predict psychological distress among workers easily, regardless of their subjective views," the researchers concluded.

Consult the investigation in the following link: https://bmjopen.bmj.com/content/11/6/e046265

Last Tweets

Digital Health Events

2022 November

Semana 1

Mon 31
tue 1
wed 2
Thu 3
Fri 4
Sat 5
Sun 6
Mon 7
tue 8
wed 9
Thu 10
Fri 11
Sat 12
Sun 13
Mon 14
tue 15
wed 16
Thu 17
Fri 18
Sat 19
Sun 20
Mon 21
tue 22
wed 23
Thu 24
Fri 25
Sat 26
Sun 27
Mon 28
tue 29
wed 30
Thu 1
Fri 2
Sat 3
Sun 4
  • No Events

  • No Events

  • No Events

  • No Events

  • No Events

Share

Digital Health in the world

  • — Science Brief: Omicron (B.1.1.529) Variant/CDC updates
    See more
  • —Coronavirus resource center/Johns Hopkins
    See more
  • — Epidemiological tracing of COVID-19 contacts / Johns Hopkins Course
    See more
  • — SARS-CoV-2 infection behavior / FCS calculator
    See more
  • — Omicron SARS-CoV-2 variant: a new chapter in the COVID-19 pandemic/ Article The Lancet
    See more
  • —Genomic Epidemiology Tracker/GISAID
    See more
  • — Mexican Genomic Surveillance Consortium
    See more
mistake: This content is protected...