Prasath Lab

AI Lab at @CincyInformatix @CincyChildrens. Deep Learning, Image Processing, Data Science, Bioinformatics.

[Prasath Lab @PrasathLab]

🔗Paper: https://t.co/esV8AeFPhO

Let’s stop just collecting/accumulating data and start curating it for the future of precision medicine. 🩺💻 9/9
#DigitalPathology #MedicalAI #GenerativeAI #DataScience #FAIRData #HealthTech #OpenScience #PrecisionMedicine #Pathology #AIReady

[Prasath Lab @PrasathLab]

Is your Medical AI actually "AI-Ready"?

This is the billion(s) $ question in the high-stakes Medical AI domain. The "dirty secret" of medical AI is that while we have more data than ever, most of it isn't ready for the prime time of Foundation Models and Generative AI! 🧵 1/9

[Prasath Lab @PrasathLab]

Key Takeaways:
•   Diversify: We must fix the geographic bias where most data comes from the Global North.
•   Standardize: A centralized portal for pathology data is no longer optional.   
•   Curate: Metadata persistence is the key to reproducible medical science. 8/9

[Mothers in Science @mothersinsci]

Applications are open for our Caregiver Travel Grant 2025! Apply now for a chance to receive flexible funding to cover caregiving expenses while attending an in-person scientific conference! Apply: https://t.co/KvROYdnUMK 📅 Deadline: March 31, 2025 #WomenInSTEM @Momademia

[Samuel Müller @SamuelMullr]

This might be the first time after 10 years that boosted trees are not the best default choice when working with data in tables.
Instead a pre-trained neural network is, the new TabPFN, as we just published in Nature 🎉

[Arvind Narayanan @random_walker]

Something I've observed in academia but I suspect is true in industry as well: as you become more senior, you'll find that you can be much more productive if you spend all your time being a manager and letting junior people do all the real work. But after a few years of this, you're likely to lose your skill at doing the work yourself, the opportunity to practice that skill, and the gratification of doing so that drew you to your chosen profession in the first place. And you'll probably also get worse at being a manager as you lose touch with the actual work.

Avoiding managerdom is hard. You have to give up substantial short-term productivity gains. If you're in academia in a tenure track, you risk not getting tenure by being less productive. And personally I find that switching between thinker mode (deep work with no distractions for a whole day) and manager mode (a thousand quick but urgent tasks) to be highly unpleasant. When I'm in thinker mode, it kills me that people have to wait a day (often a lot more) for a 1-minute response from me that could unblock them on what they're stuck on and save them hours of work. When I'm in manager mode, it kills me that I have all these creative ideas sloshing around in my brain that I'm not able to execute on.

So it's extremely tempting to perpetually be in just one mode or the other. When you have a team, not managing them is not an option, but being a pure manager is an option. That makes a constant struggle to carve out time for your own work and not give in to the temptation.

Note: I think this is only tangentially related to Founder Mode vs Manager Mode. It's much more related to another Paul Graham essay, Maker's Schedule vs Manager's Schedule. And Deep Work by Cal Newport is very relevant.

[Itai Yanai @ItaiYanai]

Expert's Dilemma: the more specialized you become, the less open you are to creative solutions from other fields. But the more you explore other fields, the more you risk losing credibility in your home field.
Interdisciplinary work is still not really embraced by academia.

[Prasath Lab @PrasathLab]

Periodic Reminder To "Be Kind" 🙂
May the Kindness Be With You 🖖

[Stephen Turner 🦋 @stephenturner.us @strnr]

A gentle introduction to pangenomics https://t.co/pbIzF1bySX

[Nature Methods @naturemethods]

Out yesterday from Baker, Sorger, and colleagues, comes CyLinter--quality control software for high-plex tissue profiling. https://t.co/Y2QRofM3DS

[antisense. @razoralign]

scAGCI: an anchor graph-based method for cell clustering from integrated scRNA-seq and scATAC-seq data https://t.co/u1PmCVLNkw

[antisense. @razoralign]

STAMP: Interpretable spatially aware dimension reduction of spatial transcriptomics https://t.co/mwzczCQPpU

[Ming "Tommy" Tang @tangming2005]

MultiSC: a deep learning pipeline for analyzing multiomics single-cell data https://t.co/25DaTOGdEK

[Christoph Bock Lab @ CeMM & MedUni Vienna @BockLab]

🗨️ WANNA TALK TO YOUR CELLS? Try out CellWhisperer – our new multimodal AI that turns single-cell RNA-seq analysis into a conversation. No coding needed, just chat in plain English. Short walkthrough below. Web app & bioRxiv preprint linked in the thread. Let's dive in! (1/9)