Jonathan Jesneck

31 posts

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Jonathan Jesneck

Jonathan Jesneck

@jonjesneck

Katılım Eylül 2009
57 Takip Edilen22 Takipçiler
Ruchi Thanawala
Ruchi Thanawala@Ruchi_TJ·
Dr. Jenkins gave a stellar presentation & was nominated for the outstanding trainee paper for his work showing the skewing in EPA data and how to fix it with utility models. Bringing real-life solutions through informatics and surged! @PhilJenkinsMD @carolynchang_MD @jonjesneck
OHSU Surgical Data & Decision Sciences Lab@OHSUSurgData

Not all EPAs are created equal! @PhilJenkinsMD shares a utility model that can help prioritize assessments when they are needed the most @APDSurgery @Ruchi_TJ @jonjesneck @kBraselDazzle @carolynchang_MD @connieygan1

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Carolyn C. Chang MD
Carolyn C. Chang MD@carolynchang_MD·
Thank you @JSurgEduc for the opportunity to share our work on EPA Assessment! EHR-integration significantly improves participation, but there is more work to be done! Looking forward to sharing more of our exciting work @APDSurgery 2025! @Ruchi_TJ @OHSUSurgData @OHSUsurgery
Journal of Surgical Education@JSurgEduc

EHR-Driven Delivery of EPA Assessments Improves Participation by Chang et al. #EHRDrivenAssessments #SurgeryEPAAssessments #Surgicaleducation #competencybasedmedicaleducation #digitaleducationtools #entrustableprofessionalactivities #practicebasedlearning pubmed.ncbi.nlm.nih.gov/38964960/

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Ashok Elluswamy
Ashok Elluswamy@aelluswamy·
We were able to achieve similar performance as the AI4 12.5 release with a relatively smaller model for AI3. Deploying the larger model requires us to implement a few kernels in the compiler to emulate the same operations that are natively supported on the AI4 hardware. The team is actively working on implementing and verifying those operations. Combined with other model compression techniques, we think we can run the same 12.5 model on both the hardware platforms in the future. That said, model parameter count is just one of the many axes of performance improvement. Dataset distribution, dataset quality, model architecture, training compute, etc., also have tremendous impact on the final performance.
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Jonathan Jesneck
Jonathan Jesneck@jonjesneck·
@alandail @elonmusk @SawyerMerritt Same. I know the Tesla tech team has a lot on their plates, but it would be a good idea to 1. Let drivers submit map issues and suggested improvements 2. Automatically track whenever actual road positions and driving paths are different from the road network data.
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Alan Dail
Alan Dail@alandail·
@elonmusk @SawyerMerritt And fix map issues, nearly all of my interventions that don't involve parking/unparking are map related caused by a handful of mapping errors in the small town I live in.
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Sawyer Merritt
Sawyer Merritt@SawyerMerritt·
NEWS: You Can Now Increase Tesla Auto Wipers Sensitivity and Autopark Can Park in Smaller Spaces. Tesla is leveraging user input to feed the neural net and machine learning models in solving Autowipers using just Vision. notateslaapp.com/news/2054/you-…
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Carolyn C. Chang MD
Carolyn C. Chang MD@carolynchang_MD·
What an honor to present our work on EHR-driven delivery of EPA assessments at @APDSurgery! With stronger collaboration between EHR vendors, DET developers and our surgical education community, we will provide better training for residents nationally.
Carolyn C. Chang MD tweet mediaCarolyn C. Chang MD tweet mediaCarolyn C. Chang MD tweet mediaCarolyn C. Chang MD tweet media
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Joseph Lo PhD
Joseph Lo PhD@JosephLo16·
30 years working at @DukeU. Including undergrad and PhD, I’ve been here for 40 of Duke’s 💯 years. Maybe it’s time to start working on my next act. 🤔🎣⛳️🏖️
Working@Duke@WorkingatDuke

Celebrating Our Duke Stars: Dr. Joseph Lo has had opportunities to work elsewhere, but he has found his home with the support and inspiration at Duke. ow.ly/Xs2I50PK2XE @DukeUBME @DukeRadiology @DukeMedSchool @JosephLo16

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American Board of Surgery
American Board of Surgery@AmBdSurg·
Dr. @kBraselDazzle, member of the ABS EPA Scope Council and former director of the ABS, shares her perspective that #EPAs will give program directors more data (a series of micro-assessments that show the progression and attainment of competency) when signing off on a trainee.
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