#medicalai

Live, measured metrics for the hashtag #medicalai from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #medicalai

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$51.02/ year · 9-character #name
Claim #medicalai — $51.02/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
5
Uses / 7 days
Mastodon
4
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 40
0.2
Avg reactions / post
Mastodon · last 40
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-10-08 00:04 UTC
1
10-02
0
10-03
0
10-04
1
10-05
0
10-06
3
10-07
0
10-08

5 uses by 4 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-10-08 00:04 UTC

Live pulse

measured · mastodon.social (Mastodon tag timeline) · fetched 2026-10-08 00:04 UTC

Everything below is measured over the latest 40 public posts (spanning ~1771 hours).

Top of the latest posts

  • "On-premise medical AI agents for reliable clinical decision-making" reports 90.04% accuracy and shows behavioral consistency can support selective autonomy by routing less reliable cases to clinician review. #MedicalAI #LLM #AIagents https

    Fritzlabs Healthcare Tomorrow@[email protected]♥ 1↻ 02026-10-07 19:28 UTCView post →
  • "Too agreeable to be accurate?" A study of 10 LLMs found that “Are you sure?” reduced diagnostic accuracy from 51.8% to 42.2%. #LLM #AI #MedicalAI #Diagnosis https://doi.org/10.1016/j.artmed.2026.103516

    Fritzlabs Healthcare Tomorrow@[email protected]♥ 1↻ 02026-10-05 06:28 UTCView post →
  • Just watched a fantastic talk at dotAI on evaluating & benchmarking AI models for a trustworthy, persistent, and safe medical assistant at #Doctolib . 6 stages, from PoC to full Orchestrator. Criteria get richer at each step: UX, medical ac

    David Aparicio@[email protected]♥ 1↻ 02026-09-17 15:50 UTCView post →

#medicalai across platforms

every network with a public tag surface

Follow #medicalai straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/medicalai