Joined August 2018
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Check our latest article published @JACEPOpen on quantitative lung pleural line characterization for #COVID19 diagnosis onlinelibrary.wiley.com/doi/… #Corona #COVID #healthcare @LsultanMD @yaletung @PennRadiology @PennMedicine @PennMedEVDCSO #POCUS @ButterflyNetInc
Amazing work
Ultrasound Radiomics in Pediatric Imaging: Current Applications, Challenges, and Future Directions Toward Clinical Implementation mdpi.com/3908404 #mdpidiagnostics via @diagnostic_mdpi @CHOP_Research @chop_pubs @oterocobo #radiomics #technology #ai #nsfwtwtًً
Ultrasound radiomics in pediatric imaging
Sharing our novel article just published: Ultrasound Radiomics in Pediatric Imaging: Current Applications, Challenges, and Future Directions Toward Clinical Implementation mdpi.com/3908404 #mdpidiagnostics via @diagnostic_mdpi @oterocobo @CHOPRadiology #radiomics #AI #healthcare @MaryamMdAl @PennRadiology
Ultrasound Research Lab@Penn (Sehgal Lab) retweeted
Advanced Techniques for Liver Fibrosis Detection: Spectral Photoacoustic Imaging and Superpixel Photoacoustic Unmixing Analysis for Collagen Tracking
mdpi.com/1424-8220/24/14/461…
#liver_fibrosis #collagen
Our study introduces cutting-edge photoacoustic imaging tools
Brain ultrasound radiomics identify subtle differences in HIV exposed children’s brain @LsultanMD #HIV #ultrasound
sciencedirect.com/science/ar…
ChatGPT can be used to detect liver disease with ultrasound. @OpenAI @LsultanMD @jmirpub @CHOPRadiology @PennRadiology #ChatGPT #healthcare @sama
Please check out our article ai.jmir.org/2025/1/e68144
Ultrasound Research Lab@Penn (Sehgal Lab) retweeted
Our researchers found that CHATGPT-4 can assist in liver ultrasound analysis by accurately distinguishing between fatty liver, fibrosis and healthy tissue. The large language model's speed and scalability show strong promise to assist with image analysis: ms.spr.ly/6013Ste7x.
ALT To be used in any crisis situation or when an urgent message needs to be shared via social.
Ultrasound Research Lab@Penn (Sehgal Lab) retweeted
🎉 Congratulations to our own Tatiana Morales for being awarded Summa Cum Laude at the 50th Annual Pendergrass Symposium! @CHOPRadiology @PennRadiology @oterocobo
Her poster, titled “Association of CEUS Perfusion Parameters with Histopathology in Pediatric Kidney Transplants,” was selected for this top honor.
📍 Join us at the poster session this afternoon to learn more about this outstanding work!
Ultrasound Research Lab@Penn (Sehgal Lab) retweeted
Study Examines Use of ChatGPT-4 for Ultrasound-based Liver Diagnostics dlvr.it/TL9SLP (mentions @jmirpub)
Ultrasound Research Lab@Penn (Sehgal Lab) retweeted
Check out our new article @jmirpub evaluating #ChatGPT4o for liver disease diagnosis on ultrasound images. Read about advantages and challenges of foundational #LLM in medical imaging. A collaboration between CHOP radiology @CHOPRadiology @CHOP_Research @ChildrensPhila and Penn Radiology @PennRadiology @KassaDarge @SudhaAnupindi @oterocobo #AI #healthcare #FutureOfAI @OpenAI @sama @TheRealAdamG @MilesKWang
@itnEditor @davidnield
ai.jmir.org/2025/1/e68144
Hot off press! ChatGPT-4 for liver disease diagnosis by ultraosound. @LsultanMD @PennRadiology @CHOPRadiology
@OpenAI @UPennIBI #OpenAI
Check out this new article ai.jmir.org/2025/1/e68144
Just published: Hydralazine‐augmented contrast ultrasound imaging improves the detection of hepatocellular carcinoma aapm.onlinelibrary.wiley.com… @VisualSonics
Ultrasound Research Lab@Penn (Sehgal Lab) retweeted
Just published: Hydralazine‐augmented contrast ultrasound imaging improves the detection of hepatocellular carcinoma aapm.onlinelibrary.wiley.com…. @URLatPenn @MBKarmacharya @Maryam34MD @CHOPRadiology @PennRadiology #TechTwitter #healthcare #ChatGPT
Please check our new publication @diagnostic_mdpi about machine deep learning and ultrasound radiomics for liver fibrosis detection at an early stage @Maryam34MD @LsultanMD @sagreiya @PennRadiology @PennMedNews @PennMDForum #Health #techno
The use of quantitative ultrasound with #machine/deep learning methods improves the detection of early fibrosis. More complex methods like multi-layer perception yielded high performance but no significant improvement over simpler ML methods.
🔗mdpi.com/2075-4418/12/11/273…
Hot of press! Our new paper published @diagnostic_mdpi Ultrasound Radiomics and deep learning for early Detection of Liver Fibrosis mdpi.com/1934214 #mdpidiagnostics via @MDPIOpenAccess @Maryam34MD @LsultanMD @sagreiya @PennRadiology @UPennIBI @PennMedicine @VisualSonics
Congratulations to our own @Maryam34MD for the acceptance of her first paper about building a predictive diagnostic model for liver fibrosis by quantitative US and deep learning learning @diagnostic_mdpi @PennRadiology @LsultanMD @sagreiya @VisualSonics @MDPIOpenAccess
Congratulations to @ryanmorrison193 for his poster presentation @sruradiology @PennRadiology
My #SRU22 poster presents an inexpensive upgrade for a diagnostic ultrasound machine to add THERAPUTIC, cancer-killing capabilities utilizing contrast-enhanced ultrasound
Published, Journal of Medical Devices: bit.ly/3s2A0r2
@sruradiology @URLatPenn
#CMIMI22 please check our own @Maryam34MD poster presentation about #machine learning for liver disease at @SIIM_Tweets CMIMI22 @LsultanMD @sagreiya @PennRadiology @VisualSonics @UPennIBI @paxerahealth #Health #TeslaAIDay siim.org/page/22cmimi_ml_ear…
#CMIMI22 please check our own @Maryam34MD poster presentation about #machine learning for liver disease at @SIIM_Tweets CMIMI22 @LsultanMD @sagreiya @PennRadiology @VisualSonics @UPennIBI @paxerahealth siim.org/page/22cmimi_ml_ear…. #Health #AI #TeslaAIDay
please check our latest paper! Can Sequential Images from the Same Object Be Used for Training Machine Learning Models? A Case Study for Detecting Liver Disease by Ultrasound Radiomics mdpi.com/1807022 #mdpiai via @AI_MDPI @LsultanMD @Maryam34MD @MBKarmacharya #Health
Hot off the press, check our new paper #AI #future #MedTwitter @LsultanMD @tedcary @Maryam34MD @MBKarmacharya @UPennIBI @PennRadiology @VisualSonics @paxerahealth @PM_Innovation @PennMDForum @PM_Innovation
To guarantee the generalizability of machine learning models, and to prevent imaging data leakage, image data acquired of the same object should be tested for independence before machine learning.
Find more details here👇
mdpi.com/2673-2688/3/3/43