this post was submitted on 16 Sep 2025
52 points (86.1% liked)

Technology

75191 readers
2508 users here now

This is a most excellent place for technology news and articles.

Our Rules

  1. Follow the lemmy.world rules.
  2. Only tech related news or articles.
  3. Be excellent to each other!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
  9. Check for duplicates before posting, duplicates may be removed
  10. Accounts 7 days and younger will have their posts automatically removed.

Approved Bots

founded 2 years ago
MODERATORS
L3s@lemmy.world
enu@lemmy.world
technopagan@lemmy.world
L4s@lemmy.world
L3s@hackingne.ws
L4s@hackingne.ws
52
Artificial Intelligence Spots Hidden Signs of Depression in Students’ Facial Expressions (www.waseda.jp)
submitted 8 hours ago by Pro@programming.dev to c/technology@lemmy.world
11 comments fedilink hide all child comments
 

cross-posted from: https://programming.dev/post/37560470

Depression is often linked to changes in facial expressions. However, the link between mild depression, known as subthreshold depression, and changes in facial expressions remains unclear. Now, researchers have investigated whether subthreshold depression shows changes in facial expressions in Japanese young adults using artificial intelligence. The findings reveal distinct muscle movement patterns related to depressive symptoms which may help detect depression early, paving the way for timely and preventative mental health care.

you are viewing a single comment's thread
view the rest of the comments
[–] ironhydroxide@sh.itjust.works 35 points 7 hours ago (4 children)

Perfect, we can now detect at what level to hold the populous so they'll keep working, and not revolt.

[–] tal@olio.cafe 2 points 3 hours ago

I recall reading that one application of sentiment analysis in voice recognition

like, determining what a speaker's mood is

is that if someone gets upset on a call talking to a computer, the system will route them to a human.

load more comments (3 replies)