Mariam Aboian Profile picture
Sep 17 8 tweets 15 min read
So true!!! Research is extremely hard and requires to be always flexible! Feeling of gratitude for my lab #ImagineQuant @YaleRadiology & my new graduates
@LeonJekel @marcvonreppert @NTillmanns @Jan_Lost_
! Tried to make this maze a little more #welcoming and you were stellar!
@marcvonreppert @SandraAbiFadel1 on imaging features of pilomyxoid astrocytomas #ImagineQuant @YaleRadiology
Guiding research can be a mix of terrifying/awesome, but if you focus on finding the best in #students & create a welcoming environment, the spark in the eyes will illuminate the way! #gratitude #peoplematter #studentsareourfuture #pureheart #growingtogether #ImagineQuant

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More from @MariamAboian

Sep 15
And the road to ⁦@MICCAI_Society⁩ ⁦@MiccaiS#Singapore has started! Cannot wait to present #ImagineQuant@YaleRadiology#BrainLesWorkshop 20 hrs travel totally worth it 😅😎❤️ to learn from the best #MICCAI22. ⁦@ujjwalbaid0408⁩ ⁦@SpyridonBakasImageImage
Goodbye #Newark #NYC, looking forward to #Tokyo in 12 hrs! Dreams do come true!!! #academiclife #neurorad Thinking of @hsairmd @sairaallapeikko @theASFNR #Maui just about now! Will have to finish that episode 13 soon! @MICCAI_Society @MiccaiStudents @WomenInMICCAI #ImagineQuant Image
Read 5 tweets
May 30
Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities mdpi.com/1648502 #mdpicancers via @Cancers_MDPI @YaleRadiology
@MerkajSara @Ryan_Bahar are an outstanding team that wrote this exciting review on application of #ML to the study of #glioma imaging. After reviewing over 12,000 articles and extracting information from over 80 articles they published their systematic review in @FrontOncology.
But, there was so much more that needed to be discussed, so @MerkajSara & @Ryan_Bahar wrote an expert review of literature with focus on future directions. @YaleMed #Neurosurgery This review is a must read when starting out in #ML & #glioma imaging #Radiomics overview
Read 8 tweets
May 15
Excited to report that @YaleRadiology @Yaleneuroradio1 #BTRG_qMIT has 14 works presented @TheASNR, with 6 of them being oral scientific presentations. @radiology_ninja @AjayMalhotraRad @SamPayabvash #physician_scientists #mentorship 1/15
@YaleRadiology @Yaleneuroradio1 @TheASNR @radiology_ninja @AjayMalhotraRad @SamPayabvash “Systematic literature review on noninvasive predicting O6 Methylguanine-DNA Methyltransferase status in Glioblastoma, using machine learning algorithms on Pre-therapy MR Imaging” Monday 5/16 9:30 am-10:45 am Gibson room @Jan_Lost_ 2/15
“Semi-Automated Longitudinal Lesion Tracking In PACS Reveals High Proportion of Metastatic Lesions Showing Mixed Response To Radiosurgery.” Beekman, Brain Tumors 1: Tuesday 1:07 pm – 1:12 pm @LeonJekel @TheASNR 3/15
Read 16 tweets
Apr 22
Available Today: Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis frontiersin.org/article/10.338… Great job @MerkajSara and @Ryan_Bahar! @YaleMed @YaleRadiology @YaleCancer
ML has been used on medical images of gliomas since early 90s but has taken off in 2017! @MerkajSara @Ryan_Bahar #BTRG_qMIT
NeuroOncology ML community is truly international! @MerkajSara @Ryan_Bahar #BTRG_qMIT
Read 7 tweets

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