Telegram RegisterThe public register of Telegram

Channel

Neuroscience & Neoplaisa Artificial Intelligence Research Group (NAIRG)

@NAIRG_ResearchGroup

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

385subscribers

+45 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001242585314
TypeChannel
Username@NAIRG_ResearchGroup
CreatedBetween 1 March 2018 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/NAIRG_ResearchGroup

Growth

340385362.56 August 2026 — 340 subscribers6 August 2026 — 340 subscribers7 August 2026 — 358 subscribers13 August 2026 — 385 subscribers6 August 202613 August 2026
4 measurements spanning 7 days, net +45. 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 333–392 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 05:36385+27
7 Aug 2026, 00:16358+18
6 Aug 2026, 21:33340no change
6 Aug 2026, 06:35340first reading

Engagement

17 posts held, back to 11 November 2025the 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
184.3%
avg views ÷ 385 subscribers
Avg views / post
710
8 posts measured
Reaction rate
0.241%
reactions ÷ views · ER floor
Posts in window
9
of 17 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 6 of 8 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 5 August 2026
Posts held17 (11 November 20255 August 2026)
Views total5,677
Reactions total12
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Aug 2026, 21:33 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

12 reactions across 6 posts, in 2 distinct kinds. The most used accounts for 83.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1083.3%
🔥216.7%

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 7 of the 17 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 12reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 17 most recent posts we hold, published 11 November 2025 to 5 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

5 Aug 2026, 06:18 UTC611 viewsread 6 August 2026
Photo

✅گواهی شرکت 🔗 لینک ثبت نام https://forms.gle/Bpz6QtDKiGFnB9yB8 NAIRG Group 📱https://t.me/NAIRG_ResearchGroup 🌐 https://nairg.org/

Signed Ali Fathi Jouzdani

5 Aug 2026, 06:15 UTCviews —

Neuroscience & Neoplaisa Artificial Intelligence Research Group (NAIRG) pinned a photo

5 Aug 2026, 06:14 UTC242 views2 reactionsread 6 August 2026

کمیته تحقیقات و فناوری دانشجویی دانشگاه علوم پزشکی شهید بهشتی و مرکز تحقیقات نوروفیزیولوژی دانشگاه علوم پزشکی بهشتی برگزار می کند 🤖🧠 کارگاه هوش مصنوعی در علوم اعصاب و سرطان 🎗💻 اگر می‌خوای با کاربرد واقعی هوش مصنوعی در پزشکی آشنا بشی، این کارگاه رو از دست نده با حضور 👨🏻‍🏫 دکتر علی فتحی جوزدانی 👨🏻‍🏫 دکتر آرمان گرجی در این کارگاه باهم مرور می‌کنیم: ✨ مفاهیم پایه هوش مصنوعی و یادگیری ماشین 🧬 تحلیل داده‌های زیستی و پز

2

Signed Ali Fathi Jouzdani

4 Aug 2026, 12:38 UTC≈4,220 views3 reactionsread 6 August 2026
Photo

🤖🧠 کارگاه هوش مصنوعی در علوم اعصاب و سرطان 🎗💻 اگر می‌خوای با کاربرد واقعی هوش مصنوعی در پزشکی آشنا بشی، این کارگاه رو از دست نده با حضور 👨🏻‍🏫 دکتر علی فتحی جوزدانی 👨🏻‍🏫 دکتر آرمان گرجی در این کارگاه باهم مرور می‌کنیم: ✨ مفاهیم پایه هوش مصنوعی و یادگیری ماشین 🧬 تحلیل داده‌های زیستی و پزشکی 🧠 کاربرد AI در علوم اعصاب 🎗 کاربرد AI در سرطان 🩻 آشنایی با MRI, EEG, fMRI 🔬 پاتولوژی دیجیتال، رادیومیکس و آینده پژوهش‌های پزشکی

3

Signed Amirhossein Moeini

31 Jul 2026, 10:36 UTC133 views2 reactionsread 6 August 2026
Photo

@NAIRG_ResearchGroup

🔥2

Signed Amirhossein Moeini

21 Jul 2026, 11:42 UTC160 views2 reactionsread 6 August 2026

🧠 NAIRG Research #Spotlight | Decoding Thyroid Nodules with Explainable AI 🔬 TU1.0 Radiomics Dictionary: Bridging Quantitative Ultrasound Features and the Clinical TI-RADS Language 📄 Article Title: A Clinically Anchored Radiomics Dictionary for Explainable TI-RADS–Based Thyroid Nodule Classification in Ultrasound; Dictionary Version TU1.0 📚 Publication Type: Original Research Article 📰 Journal: European Journal o

2

Signed Ali Fathi Jouzdani

21 Jul 2026, 11:41 UTC122 views2 reactionsread 6 August 2026

🧠 در #قاب پژوهش NAIRG | رمزگشایی ندول‌های تیروئید با هوش مصنوعی توضیح‌پذیر 🔬 فرهنگ‌نامه رادیومیکس TU1.0؛ پلی میان ویژگی‌های کمی سونوگرافی و زبان بالینی TI-RADS 📄 عنوان اصلی مقاله: A Clinically Anchored Radiomics Dictionary for Explainable TI-RADS–Based Thyroid Nodule Classification in Ultrasound; Dictionary Version TU1.0 📚 نوع اثر: مقاله پژوهشی اصیل 📰 مجله: European Journal of Radiology 📖 جلد و شماره مقاله: Volum

2

Signed Ali Fathi Jouzdani

21 Jul 2026, 11:34 UTC90 viewsread 6 August 2026

🧠 NAIRG Research #Spotlight | Explainable AI for Lung Cancer Prognosis 🔬 Semi-Supervised CT Radiomics with Limited Labels and SHAP Interpretation 📄 Article Title: Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation 📚 Publication Type: Original Research Article 📰 Journal: IEEE Transactions on Biomedical Engineering ⭐ Impact Factor: 4.4

Signed Ali Fathi Jouzdani

21 Jul 2026, 11:32 UTC99 views1 reactionsread 6 August 2026

🧠 در #قاب پژوهش NAIRG | هوش مصنوعی توضیح‌پذیر برای پیش‌بینی بقای سرطان ریه 🔬 رادیومیکس نیمه‌نظارتی CT برای پیش‌آگهی سرطان ریه با داده‌های برچسب‌خورده محدود 📄 عنوان اصلی مقاله: Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation 📚 نوع اثر: مقاله پژوهشی اصیل 📰 مجله: IEEE Transactions on Biomedical Engineering ⭐ Impact Factor: 4.4 🏅 Quart

1

Signed Ali Fathi Jouzdani

6 Jun 2026, 07:14 UTCviews —

Channel name was changed to «Neuroscience & Neoplaisa Artificial Intelligence Research Group (NAIRG)»

28 Dec 2025, 04:39 UTC252 viewsread 6 August 2026
Forwarded from @scsfanclubPhoto

سلسله سخنرانی‌های هفتگی علوم اعصاب پژوهشکده علوم شناختی پژوهشگاه دانش‌های بنیادی با همکاری پژوهشکده جامع علوم و فناوری‌های همگرای دانشگاه صنعتی شریف برگزار می‌کند: بازآرایی مغز از طریق تحریک خارجی با بهره‌گیری از شکل‌پذیری سخنران: دکتر مجتبی مددی‌ اصل تاریخ و زمان برگزاری: یکشنبه ۷ دی ۱۴۰۴ شروع ساعت ۱۵:۰۰ محل برگزاری: پژوهشگاه دانش‌های بنیادی، پژوهشکده‌ علوم شناختی (بزرگراه ارتش) حضور برای عموم آزاد است

Signed Samaneh

21 Dec 2025, 10:37 UTC175 views0 reactionsread 6 August 2026
Forwarded from @NationalBrainMappingLabPhoto

______ ┏━━━━✨️🧠 🧠NBML(National Brain Mapping Lab) ┗━━━━━━━━━━✨️🧠 آزمایشگاه ملی نقشه‌برداری مغز برگزار می‌کند: ۴۰ درصد تخفیف ویژه شب یلدا فقط تا ۱ دی 📃ویژه دوره‌های زمستان📃 کد تخفیف: yalda2025 👈👈💻کلیک کنید. 📑🖊🫆📑 💠Telegram 💠Instagram 💠LinkedIn 🌐Website با ما همراه شو🫆 ┗━━━━━━━━━━━━━━━

Signed Samaneh

Showing the 12 most recent of 17 posts we hold for @NAIRG_ResearchGroup. 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 — 17,039 of 1,345,403entries 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

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 7 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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“Neuroscience & Neoplaisa Artificial Intelligence Research Group (NAIRG)” (@NAIRG_ResearchGroup), 385 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/NAIRG_ResearchGroup.

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.