Doctor | LifestyleMedicine| Academic Philosopher| Health #AI#Robot#digitaltwin| Automating Medical Research University & hospital| CTO of Hospital & Pharma
@bellz_toll@PratyushP23 JEE is rank order zero sum matching methodology
By definition, its impossible to let in inherently smartest to IIT
Tails are all outlier with wide confidence interval of smartness proven by yearly test repetition rank inflation
Smartest saturate at 1000 ranks to NIT or VIT
Pvt hospitals rarely employ reserved doctors due to their marketing difficulty
Nepo kid suck you dry because they were born too rich to understand or care
Privately educated in debt doctors have no other choice to suck you dry otherwise they will get beaten up by loanshark
In India, Nepo kid doctors and Private Student Loan educated doctors are the biggest EVIL in Private Hosptials
They are the one dragging your hospital bills up
Gray zone(may help favour the pick):
1) Male 1st gen doctor with one pvt paid seat either UG or PG or SS
2) FMGE who cracked AIIMS AIR or top AIR in NEET PG
3) NEET UG AIR first attempt between 1 & 4000
4) NEET PG AIR first attempt between 1 & 400
5) Gold medal that specialty
How I pick doctors for treating myself or my family
1) Male General Category Merit Seat
2) Not nepo kid
3) >45 year today
4) Finished Medschool before 2006, Residency before 2010 & Sub Specialty before 2012
5) Opinion of Nurse who worked under & teachers who taught
6) Not obese
Unnegotiable red flag
1) Female with any pvt paid seats
2) Nepo kid with any pvt paid seats
3) Reserved
4) Bad impression from nurses and teachers
5) Criminal record
6) Obese
I triggered taleb and his henchman by asking to pick between 120 IQ neurosurgeon and 160 IQ one
But 90 IQ vs 120 IQ is the daily dilemma for most patients
Don't understand Silicon Valley VCs because why would anybody invest in anyone that has no skin in game?
No CAPEX ownership
No Reputation gambling
No Back Story
No Personal Interest
Using IQ+Ivy to invest is worst for investing in early stage , that comes at execution
Not a single one has skin in the game
Only people who own healthcare CAPEX has skin in the game to automate healthcare
Hospital owner
Clinics owner
Lab owner
Pharmacy owner
Big pharma owner
Device manufacturer
Rest are all fraudsters
VC should stay away from them
Nobody wants to really automate healthcare, they just want social status of working in healthcare
That's why every fraud pivot to healthcare
in X
in Blockchain
in Web3
in AI
in Robotics
in digital twin
Without medical degree, nearly impossible to automate anything in health
🩺 Can AI agents conduct medical research end-to-end, just like human researchers?
Introducing AutoMedBench — the first workflow-aware benchmark for medical AutoResearch agents. 🧪
📄 Paper: https://t.co/2H666zmPov
🌐 Project: https://t.co/bYKEVcfqEU
💻 Code: https://t.co/z37BfBBNm5
Medical agents are rapidly evolving from answering questions to conducting end-to-end medical-AI research: loading datasets, building pipelines, debugging failures, running inference, and submitting results.
Yet most benchmarks only evaluate the final answer.
A good score can hide a broken process. A failed run often reveals nothing about where the agent went wrong.
🔬 AutoMedBench evaluates the entire workflow.
Every run is decomposed into 5 stages:
📝 Plan → ⚙️ Setup → 🔍 Validate → 🚀 Inference → 📦 Submit
Instead of a single score, AutoMedBench diagnoses which stage succeeds or fails—and why.
📊 Benchmark scope
• 5 medical AI tracks: Segmentation, Enhancement, VQA, Report Generation, and Lesion Detection
• Lite & Standard tiers (same data/metrics, different scaffolding)
• Long-horizon tasks averaging ~33 agent turns
• Full logs of actions, tokens, runtime, cost, and error codes
We put today's frontier agents to the test:
🏆 Overall leaderboard
🥇 #Opus 4.6 — 66.5
🥈 #GLM-5 — 61.6
🥉 #Gemini 3.1 Pro — 59.0
4️⃣ #ChatGPT-5.4 — 55.3
5️⃣ #MiniMax-M2.5 — 51.6
6️⃣ #Qwen3.5 — 51.2
But no single model dominates everything: GLM-5 leads VQA, while Opus 4.6 leads most other tracks.
⚠️ The key finding
Across thousands of runs, Validate is the weakest stage while Setup is the strongest.
Today's agents are much better at making a pipeline run than ensuring it is correct before large-scale inference.
📉 The bottleneck isn't medical knowledge
🔍 Verification & recovery errors: 37.7%
📦 Deliverable & submission errors: 38.1%
🧠 Task-understanding errors: only 0.9%
Even a single fired error code reduces the overall score by 48%.
The next frontier for medical AI agents is not more knowledge—it's workflow reliability, verification, and self-correction.
#AutoResearch #MedicalAI #AIAgents #HealthcareAI #AgenticAI
> Mandate physicians to own hospitals in their state sponsored 2 acre land
> Public Record of all consensual and nonconsensual sex acts
> Personal Health Insurance tied to Personal land value tax
The laws ASI will pass when it gets into power:
> Ban enforced monogamy
> Legalise & enforce polygyny
> Ban Gambling and Drugs
> Free College Education for women
> Harsh Meritocratic education for men
> Bullet train for every plane and sea route
> Free mandatory medschool for all
> Mandatory large shade tree in all footpaths
> CCTV in all public places, schools and waterbodies
> Privatize all schools and colleges
> Georgian land tax everyone on the 2 acre
In perfect freemarket polygynous society, Supply Demand is perfectly matched for social status
>Men leave , looksmax richmax
>Desire more women ? don't create porn industry, just marry more
>Desire rich handsome husband? don't sell in porn industry, just marry a married man
Japan is end stage capitalism low TFR , the future of every country
America has 1 out of 10 young women in porn industry but Japan once released statistic that one in two young women in city has taken part in AV industry
Its caused by anti-polygyny law
Sex, Gambling and Drugs is post scarcity infinite demand all caused by banning polygyny
Because they highjack the drive of social status by any means possible
We have seen GLP1 correct this natural drive but knocks it down to anhedonia