2 measurements taken within a single day, net +12. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 701–717 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
10 Aug 2026, 22:18
715
+12
10 Aug 2026, 02:01
703
first reading
Engagement
20 posts held, back to 6 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
68.5%
avg views ÷ 715 subscribers
Avg views / post
490
20 posts measured
Reaction rate
0.789%
reactions ÷ views · ER floor
Posts in window
20
of 20 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 15 of 20 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 10 August 2026
Posts held
20 (6 August 2026 – 10 August 2026)
Views total
9,793
Reactions total
65
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Aug 2026, 02:01 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Reaction mix
65 reactions across 15 posts, in 4 distinct kinds. The most used accounts for 46.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
30
46.2%
👍
26
40.0%
🔥
8
12.3%
🌚
1
1.54%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 15 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 65reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 6 August 2026 to 10 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
#리브스메드
리브스메드가 수술로봇 STARK의 한국식약처 허가신청을 했네요
현재 전세계 수술로봇 시장은 intuitive Surgical(ISRG)의 수술로봇 다빈치가 독점하고 있습니다. ISRG는 다빈치 하나만 파는 기업이고 시가총액은 $133.8bil(약 188조원)에 달합니다.
최근 메드트로닉의 수술로봇 HUGO, J&J 수술로봇 Ottava가 허가 받아 다빈치 경쟁 로봇이 나오고 있으나,
진짜 게임체인저는 STARK라는 평가도 있습니다.
존스홉킨스병원 로봇수술 총괄인 아메드 가지 교수는 STARK를 "TRUE 게임체인저"라고 평가했고,
세계로봇수술학회 회장 에두아르도 파라 다빌라 박사는 “그만큼 안전하며, 유연한 기술과 구조를 갖춘 로봇 시스템은 지금껏 본 적이 없다” 라고 평가하기도 했습니다.
다빈치의 대항마가 될 기대감을…
https://www.dailymedi.com/news/news_view.php?wr_id=939000
1주일전 기사인데, 휴머노이드 로봇을 수술 보조 로봇(PA 간호사 대체)으로 사용 가능성에 대한 기사.
의료 분야에서는 수술 분야가 가정 먼저 로봇으로 전환될 분야 중 하나임
https://www.korea.kr/news/policyNewsView.do?newsId=148969679&call_from=naver_news
정부에서는 하반기 부터 보건소에서도 대학병원급 AI 진료를 위한 보급을 지원 할 예정(26년 하반기 9개, 27년 30개, 29년 72개)
고성능 AI 분석을 바탕으로 희귀·난치질환 치료제 등 혁신 신약 개발을 가속화하고, 수술 로봇 등 피지컬 AI 개발도 추진한다.
스타크가 품목허가를 획득하면 리브스메드는 복강경 수술기구부터 고급형 수술기구, 차세대 수술로봇까지 전 제품군의 국내 허가를 완성하게 된다. 올해 스타크에 전사적 역량을 집중해온 만큼 연내 허가 획득을 목표로 식약처 심사 절차에 적극 대응할 계획이다.
다수의 글로벌 KOL(Key Opinion Leader)이 직접 발표에 나서 스타크의 기술적 특성과 전임상 연구 결과를 조명하고 차세대 수술 로봇으로서의 가능성에 주목했다.
[고스트로보틱스 CEO "미국에 팔린 중국산 로봇, 스파이웨어 탑재됐다"폭로]
- LIG넥스원의 미국 자회사 고스트로보틱스의 개빈 캐넬리 CEO가 미국 내 보급된 중국산 로봇에 능동적이고 의도적인 스파이웨어가 배치되어 작동 중이라고 폭로
- 미 당국의 외국산 로봇 규제 조치와 맞물려 미·중 기술 패권 경쟁이 AI 및 로봇 산업 전반으로 전면 확대되는 양상
- 그는 중국 로봇 업계의 가격 정책도 강하게 비판
- 캐넬리 CEO는 "시장 내 약탈적 가격 책정의 사례가 차고 넘친다"며 "이는 단순히 미국과 중국 로봇 기업 간의 상업적 경쟁이 아니라, 미국의 민간 기업과 중국의 조직적인 국가 전략 간의 대결"이라고 언급
- 캐넬리 CEO는 "오늘날의 규제 발표가 더 강력한 사이버 보안을 유도하고 공정한 경쟁 환경을 만든다면 고객과 로봇 산업 …
Showing the 12 most recent of 20 posts we hold for @livsmed. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank
Citation-graph rank — 1,050,911 of 1,481,217entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 August 2026 — this
entry's latest reading, not the date you are reading this.
“리브스메드” (@livsmed), 715 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/livsmed.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.