Telegram RegisterThe public register of Telegram

Channel

Нейросети для врачей | Нейросети в медицине | MD.school

@mdai_dima

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

12,610subscribers

+108 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001721416626
TypeChannel
Username@mdai_dima
CreatedBetween 1 December 2021 and 31 March 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live12 August 2026
Measurements held7
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/mdai_dima

Growth

12,50212,61012,5567 August 2026 — 12,502 subscribers7 August 2026 — 12,503 subscribers8 August 2026 — 12,523 subscribers9 August 2026 — 12,548 subscribers10 August 2026 — 12,568 subscribers11 August 2026 — 12,586 subscribers12 August 2026 — 12,610 subscribers7 August 202612 August 2026
7 measurements spanning 5 days, net +108. 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 12,486–12,626 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 15:3312,610+24
11 Aug 2026, 15:5112,586+18
10 Aug 2026, 19:1812,568+20
9 Aug 2026, 16:3312,548+25
8 Aug 2026, 14:2312,523+20
7 Aug 2026, 11:3612,503+1
7 Aug 2026, 08:0112,502first reading

Engagement

15 posts held, back to 30 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 15 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
4.75%
avg views ÷ 12,610 subscribers
Avg views / post
599
15 posts measured
Reaction rate
1.24%
reactions ÷ views · ER floor
Posts in window
15
of 15 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 12 August 2026
Posts held15 (30 July 202612 August 2026)
Views total8,985
Reactions total111
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 12:20 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.

What this channel posts

Video runtime
1m 56s
Average length
58s

Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

111 reactions across 15 posts, in 5 distinct kinds. The most used accounts for 68.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
7668.5%
🔥2118.9%
👍65.41%
👌43.60%
🙏43.60%

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 15 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 111reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 30 July 2026 to 12 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.

Recent posts

11 Aug 2026, 07:07 UTC381 views7 reactionsread 12 August 2026
Photo

Один шаблон запроса для трёх врачебных специальностей: показываем, что именно нужно менять Готовый промт без изменений редко может подойти всем. Один и тот же запрос даст разные результаты для терапевта, педиатра и невролога. Потому что меняются пациент, клиническая задача, источник информации и формат готового материала. Разберём на примере 👇 Базовый шаблон «Ты — врач [специальность] и медицинский редактор. На осн

👍32🔥2

9 Aug 2026, 08:16 UTC654 views34 reactionsread 12 August 2026
Video

😏 Делаем разминку для мозга ставьте: 🔥, если видео реальное ❤️, если это генерация ИИ Видео канала Технологии | Нейросети | Боты

32🔥2

8 Aug 2026, 07:20 UTC613 views7 reactionsread 12 August 2026
Photo

Почему врачи «тормозят» с нейросетями? Потому что у них нет времени разбираться ещё в одном сложном инструменте. 😥 Самостоятельное обучение часто выглядит так: открыть несколько сервисов → написать случайный запрос → получить общий ответ → потратить время на исправление → вернуться к ручной работе. 👊 На курсе «Нейросети в работе врача» всё иначе. ➕ Курс создал врач. ➕ Преподаватели — врачи, которые понимают специф

5👌2

7 Aug 2026, 07:25 UTC673 views4 reactionsread 12 August 2026
Photo

Еще 3 нейросети для врачей, которым можно доверять (Часть 2) 📌 Сохраняйте в закладки. На прошлой неделе мы начали разбирать ИИ-инструменты, которые работают строго с научными базами и не придумывают факты (если пропустили первую часть — обязательно загляните в предыдущий пост!). Как и обещали, публикуем продолжение подборки. 🔵 ResearchRabbit — находит связанные публикации и визуализирует связи между исследованиями,

2🔥2

5 Aug 2026, 09:11 UTC635 views6 reactionsread 12 August 2026

Коллеги, если июль прошёл между статьями, клинреками, презентациями и поиском способов быстрее справляться с привычными задачами — сохраняйте эту подборку. 🔥 Мы собрали самые полезные инструкции месяца: для научной работы, подготовки докладов, разбора клинических рекомендаций и повседневной практики врача. НАУКА, СТАТЬИ И ДОКЛАДЫ ➡️ Как подготовить доклад на врачебную конференцию: промпты для работы с нейросетями

3🔥3

4 Aug 2026, 11:13 UTC567 views6 reactionsread 12 August 2026
Photo

Только в августе: выберите ОДИН из трёх курсов бесплатно Нейросеть может за несколько минут найти исследования, структурировать данные, подготовить черновик документа или помочь с переводом статьи. Но максимальную пользу она приносит врачу, который умеет проверять информацию, читать статистику и работать с англоязычными источниками. Поэтому с 1 по 31 августа при покупке курса «Нейросети в работе врача» мы дарим оди

4🔥2

3 Aug 2026, 13:21 UTC624 views3 reactionsread 12 August 2026
Photo

14 полноценных образовательных программ для врача за 1 990 ₽ в месяц 🔥 • Подготовиться к защите диссертации. • Подтянуть медицинский английский. • Освоить новую профессию и выйти на дополнительный доход. Для каждой из этих целей больше не нужно покупать отдельный курс. В новой подписке «МД ресурс» — Медицинский английский, доказательная медицина, статистика, научные публикации, диссертация, академическое письмо

2🔥1

2 Aug 2026, 07:10 UTC757 views4 reactionsread 12 August 2026
Photo

🎁 Дарим памятку - молодым коллегам и всем, кто пишет диссертации или просто читает исследования! 💾Обязательно к сохранению Памятка по скрининговой оценке статьи: 35 простых вопросов, которые превращают хаотичное чтение в системный фильтр. ➡️Освоив этот алгоритм, вы перестанете тратить вечера на статьи, которые не стоят даже заголовка. ‼️ А ещё здесь собрана подборка постов по теме — от ловушек диссертационных сове

4

1 Aug 2026, 15:18 UTC743 views1 reactionsread 12 August 2026
Photo

Доктор, кидайте кости... 🎲 Сыграйте в мини-игру. Простой способ получить напутствие для рефлексии выходного дня. Как играть: ➤ Кидайте кубик 🎲 в комментариях ➤ Читайте свой пункт ниже. ➤ Ставьте реакцию: попало в цель или мимо? ⭐️Ты внимателен к деталям — и это твоя суперсила. Нейросети помогут быстрее структурировать мысли, а глубина анализа останется твоей. Умный врач + умный инструмент = двойная точность. ⭐️Ты

1

Showing the 12 most recent of 15 posts we hold for @mdai_dima. 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 — 156,015 of 1,151,006entries 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.

Mentions

Named by 3 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Нейросети для врачей | Нейросети в медицине | MD.school” (@mdai_dima), 12,610 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/mdai_dima.

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.