Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 19 September 2026 and assigned it the closest of 31 fixed categories, at 99% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
7 measurements spanning 42 days, net +538. 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 332–1,032 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
18 Sept 2026, 12:56
951
+129
9 Sept 2026, 07:18
822
+76
31 Aug 2026, 13:41
746
+107
24 Aug 2026, 09:47
639
+207
16 Aug 2026, 17:09
432
+19
8 Aug 2026, 05:34
413
no change
7 Aug 2026, 19:44
413
first reading
Engagement
20 posts held, back to 20 July 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
1h 00m
Average length
15m 15s
Measured directly from 4 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
69 reactions across 14 posts, in 3 distinct kinds. The most used accounts for 95.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
66
95.7%
👍
2
2.90%
👎
1
1.45%
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 14 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 69 reactions 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 20 July 2026 to 7 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.
قسمت های دوم و سومش رو هم دکتر کامران احمدی منتشر کردن براتون فرستادم حتما ببینید
قسمت دوم در مورد یک تست شخصیت شناسی و کلا اهمیت بسیار زیاد شخصیت در انتخاب رشته دستیاری هست
و قسمت سوم هم در مورد ده اشتباه رایج رزیدنت ها که باعث میشه دوران رزیدنتی خوبی نداشته باشن
https://www.instagram.com/reel/DbvIpd5KQ3j/?igsh=dDBtb2g5ams5OWRn
خودم به شخصه چندین بار تفاوت های این دوتا رو به خاطر سپردم و باز فراموش کردم ولی خب یه بار که یه ذره دقیق تر بررسی کردم دیدم خیلی نیازی به حفظ کردن نداره میشه راحت یاد گرفت
دارم یک کتابی مطالعه میکنم تحت عنوان «استدلال بالینی: مفاهیم، آموزش و ارزیابی»
و واقعا کتاب خفنیه، پیشنهاد میکنم حتما مطالعه بکنید. این بخش از متنش رو که گذاشتم برای اینه که متوجه بشید چرا خیلی مواقع با خوندن رفرنسهامون نمیتونیم اونطور که باید و شاید به تشخیص برسیم
علت اینه که استدلال بالینی یک روند پیچیده و تو در تویی داره که ما با خوندن کتابایی مثل هریسون و سیسیل و ... فقط به بخشی از این مهارت مسلط میشیم و بخش ز…
رفقا همونطور که اینجا چیزی تحت عنوان تجربیات_استاژری راه انداختیم و خیلی از بچه ها خداروشکر استفاده کردن و میکنن (دم تک تک کسایی که فیدبک دادید گرم واقعا)
تصمیم گرفتم توی اینستاگرام یه چیز دیگه راه بندازم تحت عنوان #تجربیات_بالینی و دلم میخواد اونجا توی حالا کشیک هایی که وامیستم یا چیزایی که توی بخش میبینم و کلا در بالین چیزایی که اتفاق میافته اگر بار آموزشی داشته باشه توی استوریای اینستاگرام مدیکولوژی به اشتراک ب…
❓ موضوع افزایش ظرفیتهای رشتههای پزشکی به کجا انجامید؟
❓افزایش ظرفیتهای رشتههای پزشکی، دندانپزشکی و داروسازی چه پیامدها و شرایطی را درپی داشته است؟
❓در آخرین جلسه شورای عالی انقلاب فرهنگی در خصوص این موضوع چه تصمیمی گرفته شد؟
دکتر طاهره چنگیز معاون آموزشی وزارت بهداشت، درباره جزئیات این موضوع در «برنامه کشیک سلامت» شبکه سلامت سیما توضیح میدهد.
🔻مشروح گفتگوی مجری برنامه کشیک سلامت شبکه سلامت سیما را با معاون آ…
همیشه توی تروما خوندیم که FAST باید انجام بشه که ببینیم بیمار خونریزی داره یا نه
ولی شاید خیلی کسی نگفته چطور اصلا اون پروب رو استفاده بکنیم، توی این ویدیو مختصر در موردش صحبت کردم
چطور بفهمیم بیمار خونریزی داخلی داره یا نه؟
https://www.instagram.com/reel/DbnaNvfK_u5/?igsh=MWtpZnAwN2VydmQ4Nw==
بچه ها این ویدیو رو من از کانال دکتر کامران احمدی برداشتم مربوط به انتخاب رشته دستیاری هست
درسته که خب من هنوز به شخصه خیلی فاصله دارم با این آزمون ولی خیلی نکات خوب و آموزنده ای داخلش هست و پیشنهاد میکنم حتما ببینید چون میتونه دیدگاهتون رو به انتخاب رشته تغییر بده
صحبت هایی که انجام میدن کاملا علمی و بر اساس مقالات و مطالعات هست
❤3
Showing the 12 most recent of 20 posts we hold for @Medicology_ABZUMS2. 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.
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.
Mentions
Named by 1 registered channel — 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.
Named by
Channels on the register whose posts name this channel's handle.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“مدیکولوژی | بالین | Medicology” (@Medicology_ABZUMS2), 951 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/Medicology_ABZUMS2.
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.