endovelicus

neurology neuroinformatics

[endovelicus @datagz]

@skdh @WKCosmo It's obvious. He stated that he enjoys paddling and pivoting across the interstitial fluid of our brain cells.

[endovelicus @datagz]

@skdh That is highly significant because it would explain how logical thinking can also leak into parallel dimensions.

[endovelicus @datagz]

@CsfHighlan97034 Great job. Please, could you provide the reference IDs for these siblings in the v66 dataset?

[Eric Topol @EricTopol]

The effect of current anti-amyloid drugs vs Alzheimer's disease is "trivial" for cognitive function or dementia severity, not clinically meaningful, from a systematic @cochranecollab review of 17 trials, >20,000 patients
https://t.co/9A6PeZOyAt

[Sumanth @Sumanth_077]

Fine-tuning massive LLMs used to be painfully slow, but not anymore!

4 open source libraries that accelerate fine-tuning of Large Language Models

1. Unsloth AI

• Fine-tune models like Qwen3, Llama 4, and Gemma 3 up to 2× faster with 70% less VRAM
• Uses optimized Triton kernels and manual backprop for exact accuracy
• Supports low-resource setups and runs on consumer GPUs or even Colab/Kaggle with ~3 GB VRAM

GitHub repo → https://t.co/n2aa7vWE1v

2. LLaMA Factory

• Fine-tune over 100 models (LLaMA, Mistral, Gemma, etc.) using a simple CLI or WebUI
• Supports LoRA, QLoRA, full or frozen fine-tuning across 2–8‑bit precision
• Includes built-in dataset templates, training monitors, and model export options

GitHub repo → https://t.co/Zrbg95fXpy

3. DeepSpeed

• Built for large-scale distributed fine-tuning with ZeRO and FSDP
• Optimized for multi-GPU and multi-node training with advanced memory management
• Trusted in production environments for scalable LLM training

GitHub repo → https://t.co/OekS5EZU2Z

4. Axolotl

• Yaml-based setup for fine-tuning, LoRA/QLoRA, DPO, GRPO, and multimodal workflows
• Includes kernel optimizations for memory-efficient training
• Actively maintained with support for Hugging Face, model export, and inference

GitHub repo → https://t.co/tUQ2W1Kpcl

[Antonio Lupetti @antoniolupetti]

This is Algebrica. A mathematical knowledge base I’ve been building for 2.5 years.

215+ entries, carefully written and structured.

400k+ views over this time. Not much in absolute terms, but meaningful to me.

No ads.
No courses to sell.
No gamification.
No distractions.

Just essential pages, aiming to explain mathematics as clearly as possible, for a university-level audience.

Built simply for the pleasure of sharing knowledge.

Content licensed under Creative Commons (BY-NC).

Best experienced on desktop.

If it helps even a few people understand something better, it’s worth it.

[International Journal of Stroke @IntJStroke]

🫀 🧠 CATCH-AF score provides a robust, interpretable, and easily applicable tool for predicting atrial fibrillation after ESUS

👉 ✅ Supports targeted & cost-effective rhythm monitoring

Read about CATCH-AF here! ⬇️
https://t.co/clol5WMqk2 @luciodanna2

[Oren Gottfried, MD @OGdukeneurosurg]

Sciatic nerve from doc simplifies.

[tuōmo @7uomoki]

Genome analysis with AI is cool i guess - but a simple CLI wasn't enough for me.

Introducing HGI (Human Genome Interface):

HGI connects agents to highly optimized bioinformatics tools, performing a full genome analysis in ~1 minute (!) on a MacBook Pro. It identifies both known and novel high-risk variants, all analyzed by LLMs.

Compressing the pipeline from the original >60 minutes down to this timeframe was an exciting computer science and bioinformatics challenge. Thrilled with the results, as the current framework enables a genuine "talk to your genome" experience.

HGI significantly boosts AI capabilities, as LLMs typically struggle with standard genetics and bioinformatics tools and tasks.

Currently for research purposes only, but open for inquiries.

[Scholarship for PhD @ScholarshipfPhd]

40 Free Data Analysis & Visualization Tools for Researchers

1️⃣ R
2️⃣ Python (Pandas, NumPy, Matplotlib)
3️⃣ JASP
4️⃣ Jamovi
5️⃣ PSPP (SPSS Alternative)
6️⃣ Orange Data Mining
7️⃣ KNIME
8️⃣ Datawrapper
9️⃣ Chart.js
🔟 Plotly

1️⃣1️⃣ ggplot2 (R)
1️⃣2️⃣ Seaborn (Python)
1️⃣3️⃣ D3.js
1️⃣4️⃣ Power BI (Free Version)
1️⃣5️⃣ Google Data Studio (Looker Studio)
1️⃣6️⃣ Tableau Public
1️⃣7️⃣ RawGraphs
1️⃣8️⃣ Gephi (Network Analysis)
1️⃣9️⃣ Cytoscape
2️⃣0️⃣ QGIS (Geospatial Analysis)

2️⃣1️⃣ Excel (Advanced Features)
2️⃣2️⃣ Google Sheets (Data Analysis Add-ons)
2️⃣3️⃣ Stata (Free Trial)
2️⃣4️⃣ SAS University Edition
2️⃣5️⃣ SPARK (Big Data)
2️⃣6️⃣ RapidMiner
2️⃣7️⃣ WEKA
2️⃣8️⃣ Bokeh (Python)
2️⃣9️⃣ Flourish
3️⃣0️⃣ VOSviewer (Bibliometric Analysis)

3️⃣1️⃣ Scipy (Python)
3️⃣2️⃣ Statwing
3️⃣3️⃣ TensorFlow
3️⃣4️⃣ Scikit-learn
3️⃣5️⃣ IBM Watson Analytics
3️⃣6️⃣ Apache Superset
3️⃣7️⃣ PolyAnalyst
3️⃣8️⃣ Metabase
3️⃣9️⃣ Infogram
4️⃣0️⃣ Google Charts

📌 Save & Share with fellow researchers!
#PhDLife #DataScience #DataVisualization

[Lea Alhilali, MD @teachplaygrub]

This one's for me!!

I was tired of seeing small MCA infarcts that were clearly from a branch occlusion& not knowing the name of the branch that was occluded!

I decided I would find a way to remember these territories myself-and then share it w/ you!!

Here's how you can remember the different territories

Start w/4 cardinal territories
-These are the skeleton from which you can remember the rest

Orbitofrontal: Easy, it overlies orbit in the frontal region, like its name

Central: East, it's the territory surrounding central sulcus

Angular: Easy, it literally looks like an angle between parietal & temporal region

Polar: Easy, it's the temporal pole!

Bc it's the MCA, there is an M or two humps between each of these cardinal branch territories & their names reflect the anatomy

Finally, the temporal territories look like fingers on a hand:

Polar is the thumb of the hand: remember polar sounds pollex which means thumb

Middle temporal is literally the middle finger!!

Now you know the middle cerebral branch territories— so your reports will never be middling!

[Prof Tom Solomon CBE @RunningMadProf]

Proud to support F.L.A.M.E.S. from @encephalitis

Early recognition of Flu-like symptoms, Loss of consciousness, Acute headache, Memory issues, Emotional changes & Seizures can save lives.

Spread awareness & support: https://t.co/mSuMxnIYaJ

[MedicoNotes @MedicoNotes]

🧠 Approach to Coma

A structured guide for evaluating a nonresponsive patient with decreased consciousness.

⸻

1️⃣ Rule Out Systemic Causes
Begin by excluding common metabolic, toxic, or infectious causes of altered mental status.
➡️ Refer to AMS (Altered Mental Status) protocol.

⸻

2️⃣ If Preceded by Trauma
➡️ Perform non-contrast head CT
• Epidural Hematoma – Biconvex/lens-shaped bleed
 → Requires neurosurgical decompression
• Subdural Hematoma – Concave/crescent-shaped bleed
 → Needs serial imaging and neurological exams

⸻

3️⃣ Focal Neurological Signs Present
➡️ Proceed with non-contrast head CT
• Intracerebral Hemorrhage – Intraparenchymal bleeding
 – Manage BP, reverse coagulopathy, elevate head >30°, correct sodium
 – Watch for ↑ ICP (Cushing’s Triad) → May require neurosurgical intervention

• Subarachnoid Hemorrhage – Blood in subarachnoid space
 – Treat with IV osmotherapies, hyperventilation, and sedation

⸻

4️⃣ Vertical Eye Movements Spared
➡️ Suspect Brainstem lesion
• Head CT may show brainstem hemorrhage
• CTA/MRA may confirm Basilar Artery Stroke
 → Requires urgent stroke management and airway protection

⸻

5️⃣ Consider Lumbar Puncture
• Xanthochromic CSF ➜ Suggests Subarachnoid Hemorrhage
• CSF abnormalities (WBC ↑, protein ↑, glucose ↓) ➜ Think Meningitis
• If venous thrombosis suspected → Perform CTV/MRV
 → May reveal Venous Sinus Thrombosis → Treat with anticoagulation

⸻

📌 Learn more high-yields neurology topics from our website:
🌐 https://t.co/2UQyCbb6in

⸻
#MedicalEducation #USMLE #neurology #ClinicalMedicine #InternalMedicine

[Python Programming @PythonPr]

The Math Needed for AI/ML (Complete Roadmap)
https://t.co/xroBNMA7kc

[𝗿𝗮𝗺𝗮𝗸𝗿𝘂𝘀𝗵𝗻𝗮— 𝗲/𝗮𝗰𝗰 @techwith_ram]

Deep Learning with PyTorch step by step

Total 3 volumes:

- Vol.1 (Fundamentals)
- Vol.2 (Computer Vision)
- Vol.3 (Sequences and NLP)

Official Repo: https://t.co/AdxIJjJc4t

[Jeremy Leipzig @jermdemo]

OK, so the $ bio ai assistants are:

Ascent Bio - https://t.co/r9XxxvizqF
Bio Protocol BIOS - https://t.co/ZlU7ueQgzT
Edison Scientific - https://t.co/qioORKVhhG
K-Dense - https://t.co/06tuwxhbsA
Potato - https://t.co/I4mcR5vhPL
SciSpace - https://t.co/4jD6wq5ufn

Did I miss any?

[David Brang @DavidJBrang]

EEG requires many neurons aligned so that their electric fields can positively sum to spread up to the scalp. I made a browser-based simulator for my EEG class to visualize how "open fields" contribute to EEG recordings.
https://t.co/AIVPTI7A9p
Github: https://t.co/zoFjD4joIq

[Tom Dörr @tom_doerr]

Resources for running LLMs on local hardware

https://t.co/LNDKQzn8f3

[Daily Dose of Data Science @DailyDoseOfDS_]

NN-SVG: Create neural network architecture drawings parametrically!

Export them to SVG files and use them in your work!

[TensorTonic @TensorTonic]

Module for Graph Theory in Machine Learning is live!

this includes fundamentals to -

> computational graph (how pytorch works)
> Graph representation
> GNNs
> Message Passing in GNNs
> Spectral graph theory
> random walks & markov chains