Hiesinger Lab

We are excited to announce 🔥EchoAI-Peds 🔥, the first multi-task deep learning model for pediatric #echofirst analysis. It's been a pleasure to lead this alongside @mrudangm14 under the guidance of @hiesingerlab and in close collaboration with @jolleylab. Link below⬇️ [1/n]

✨Featured Article ✨in @atvbahajournals May issue! Chemokine (C-C motif) Ligand 2 Expressing Adventitial Fibroblast Expansion During Loeys-Dietz Syndrome Aortic Aneurysm Formation. Authors inc. @ardalal_MD @ajpedroza_md @HiesingerLab, Fischbein Lab, et al ow.ly/B3vJ50VNheY

A huge congratulations to super-🌟 med student and @HiesingerLab member @dhamank24! 🥳

I’m making the model weights for our foundational CMR vision encoders (see pinned post) available free for academic use. Paper still in peer review, but can’t wait to see what everyone builds with this! Git: github.com/rohanshad/cmr_… Weights: huggingface.co/rohanshad/cmr_… #HNY2025

The Hiesinger Lab @stanfordctsurg is at #AHA24! Catch lab members @rohanshad and @dhamank24 presenting their work on uncovering hidden HCM diagnoses in the UKBioBank using deep learning for CMR🫀🧲💻🤖 Where: S104A When: 4:00 - 4:10 pm (CT), Nov 17

Had a great time talking about finite elements and generative AI in medicine at @BmeSjsu Pathways Seminar last week! Many thanks to my dear friend Prof. @EllaSugerman for the invite and to my @HiesingerLab mates @joseph_cho1 and @cyrilzakka for sharing their great results 🔥

🔥New preprint alert🔥 We're excited to share an early preview of 𝗦𝘂𝗿𝗚𝗲𝗻, a text-diffusion model for generating surgical videos! This model can generate videos of higher quality (720x480) & longer duration (49 frames) than the current SoTA. Great work by @joseph_cho1!

Two years ago to the day, I joined the @HiesingerLab at Stanford Medicine, and now it’s time for me to wrap up this chapter of my life! 🎓 Reflecting back, I see a tapestry of efforts—my family's unwavering support, my friends’ continuous encouragement, my own growth—and some luck along the way. It truly does take a village, and I'm grateful for every part of mine. It goes without saying that I’m grateful to both @rohanshad and @HiesingerLab for believing in me every step of the way, and always encouraging me to lead my own projects and find my own voice, despite many of the obstacles we faced. I’m also lucky to have met some truly impactful people whose work over the years has heavily influenced my own research direction, many of whom have also taken it upon themselves to guide me along the way, namely @Dr_ASChaudhari @RoxanaDaneshjou @curtlanglotz @DrAalami @pranavrajpurkar @euanashley @ardalal_MD and many more! Excited for what’s next!

In case you missed it, our team in collaboration with @Dr_ASChaudhari, @RoxanaDaneshjou, @DrAalami, and @vishnuravi defined a framework for autonomous EHR systems, and implemented the first Level 1 EHR system with retrieval and extractive capabilities! Check it out!

I’m giving a few talks on GenAI in Health in the next few months to technical founders and practicing clinicians across the US. Would love to highlight some open source medical AI projects in my slides and am looking for some suggestions. /cc @Michael_D_Moor @katieelink

Catch our postdoc @cyrilzakka presenting our work on Almanac at the @StanfordHAI Five event today! Also a great lineup of speakers!

Introducing MediSyn, a pair of text-guided diffusion models for generating high-fidelity and diverse medical 2D and 3D images across medical specialties and imaging modalities. arxiv.org/abs/2405.09806 1/n

Exciting week! We're also releasing an early preview of MediSyn, a family of text-diffusion models exploring the potential for generative models to synthesize medical data across many modalities (2D and 3D) and specialties (dermatology, radiology, pathology, GI, ophthalmology, surgery and more) We're still exploring different techniques to improve text alignment and generation quality but this is a great first step!

Super excited to showcase our newest work Almanac Copilot an EHR agent capable of answering questions about your patients and placing orders for you across any modern EHR system. Background: Nearly 75% of clinicians with burnout symptoms pinpoint EHRs as a source due to poor usability or workflow integration. Methodology: We train a 33B LLM to perform open-ended QA on patient information, as well as order placement using the FHIR interoperability standard (cc @zakkohane , @AdamRodmanMD) Result: Almanac Copilot obtains a success rate of 74% across 300 common EHR tasks based on MIMIC-IV. Your very own personal EHR assistant!

April* (but it does feel like a lifetime!)

@arxiv our manuscript has been on hold since March 30. Is there anything we can do to help streamline this process? submit/5569805

New Original Article: Augmenting LLMs with knowledge databases (e.g., browser, calculators) demonstrated improved factuality, safety, completeness, and physician preference when compared to other models. Read the full study by @cyrilzakka and others: nejm.ai/42gpqhM

Can patients at risk for RV Failure after LVAD implantation be identified before LVAD therapy? Check out our @JAMAcardio publication: jamanetwork.com/journals/jamac… Review thread below. @Joseph_Taleb @CPKyriakopoulos @JamesCFangMD @PalakShahMD @HiesingerLab @preventfailure @JosefStehlik

Huge congratulations to Dr Jennifer Romano! Our first (living) female president of the ⁦@STS_CTsurgery⁩ #sts2024. The organization is in incredibly good hands! Looking forward to 2024 program year ⁦@WomenInThoracic⁩

Our research on ‘Almanac: Retrieval Augmented LLMs for Clinical Medicine’ is finally out on @NEJM_AI! We demonstrate that LLMs augmented with tools (browser, calculators) outperform ChatGPT-4 & others on a novel dataset of 300+ questions assessed by board-certified physicians!