Kolachalama laboratory @vkola_lab
Associate Professor @BUMedicine @BUCompSci | Founding Member @BU_CDS vkola-lab.github.io Massachusetts, USA Joined August 2016-
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Our lab's latest work introduces a groundbreaking approach to #cancer survival prediction, merging #pathology images & gene expression data with a graph attention-based fusion architecture. Published in IEEE Transactions on Medical Imaging! @BUMedicine @BU_CBM @BUCompSci @BU_CDS
Our lab's latest work introduces a groundbreaking approach to #cancer survival prediction, merging #pathology images & gene expression data with a graph attention-based fusion architecture. Published in IEEE Transactions on Medical Imaging! @BUMedicine @BU_CBM @BUCompSci @BU_CDS
Explore the intricacies of an attention-based fusion model that innovatively combines pathology image graph representations with gene expression data to enhance survival predictions for lung cancer patients, outstripping current multimodal methods. ieeexplore.ieee.org/document/10494…
🚀 New paper! GRAPE-Net, our novel computational model, excels in stratifying lung tumors & bronchial lesions, aiding early detection & treatment strategies. Discover the full study: @AJPathology doi.org/10.1016/j.ajpa… #LungCancer @BU_Tweets @BUMedicine @BUCompSci @BU_CDS
Our latest study in @SkeletalRadiol explores how subchondral bone length, a novel #MRI-derived measure, can predict the need for total #knee replacement due to #Osteoarthritis.🦵🔬 doi.org/10.1007/s00256… With @ProfDeepakKumar @TDCapellini @BUMedicine @BU_CDS @BUCompSci @BU_CBM
In a @BU_Tweets #HTAN supported study, @rushin_gindra, @vkola_lab, et al. developed a computational pipeline for whole-slide H&E images to differentiate between bronchial #premalignant lesions by progression status @biorxivpreprint biorxiv.org/content/10.110…. #LCSM
This study shows that collecting smartphone application data in an unsupervised, remote, and naturalistic setting in a large, community‐based population is feasible. #AHAJournals #JAHASpotlight @PSunderaraman @Ileana_DeAndaD @vkola_lab ahajrnls.org/3HppTnZ
The future of patient monitoring is using passive data collection. But how do we get to that goal in our patients with #Alzheimer Disease? Find out in this #AHAJournals #JAHASpotlight #Review from @Ileana_DeAndaD @PSunderaraman @ludyshihmd @vkola_lab ahajrnls.org/3RVQSwc
Free to read: Large Language Models in Neurology Research and Future Practice bit.ly/3Gr3xC6 #NeuroTwitter #AI
Pleased to share 2 preprints on our latest work in Alzheimer's 🧠🤖 doi.org/10.1101/2023.1… A dual-objective framework to reconstruct high-quality brain MRIs & retain critical disease features 🧠🔍 doi.org/10.1101/2023.0… Disease-driven domain generalization in medical imaging
Join the #ResearchOnTap conversation about Health Data Science. Hear from @BUexperts on how #DataScience can shape #Healthcare practices, policies and our understanding of the world. Host: Debbie Cheng, @BUSPH Population Health Data Science Program ➡️ spr.ly/6013u0Sn1
Dr. Jennifer Beane and @vkola_lab et al. @BU_CBM #HTAN created a computational pipeline for bronchial #premalignant lesion stratification to identify those at risk of #LungCancer progression @biorxivpreprint biorxiv.org/content/10.110…. #LCAM #LCSM
Does your Machine Learning project require the creation of different classes of annotation on large biomedical images? See how PixelView lets you customize and color code annotations pixelview.deeppath.ai #MachineLearning #DigitalPathology
PixelView, a web-based tool for digital pathology is available to try out for free. Please check this post and retweet. #DigitalPathology #WholeSlideImaging #Pathology #Digital #ComputationalPathology #MachineLearning #DeepLearning #Histology #Microscopy #SlideScanner #Imaging
PixelView, a web-based tool for digital pathology is available to try out for free. Please check this post and retweet. #DigitalPathology #WholeSlideImaging #Pathology #Digital #ComputationalPathology #MachineLearning #DeepLearning #Histology #Microscopy #SlideScanner #Imaging
Comparison of multiple H&E images is a common requirement when generating annotations necessary for downstream machine learning. PixelView enables Web-based side-by-side image display for collaborative annotation. Free trial available at: pixelview.deeppath.ai
New in @GreenJournal by first author Dr. Michael Romano of @UCSFimaging & colleagues from @BUMedicine, @BU_ece: Large Language Models in Neurology Research & Future Practice. n.neurology.org/content/early/…
Thrilled to see this online! With Mike Romano @UCSFimaging @RadsUcsf @ludyshihmd @YPaschalidis #LLM @BU_CBM @BUMedicine @BU_CDS @BUCompSci @BU_Tweets @BUCollegeofENG
Thrilled to see this online! With Mike Romano @UCSFimaging @RadsUcsf @ludyshihmd @YPaschalidis #LLM @BU_CBM @BUMedicine @BU_CDS @BUCompSci @BU_Tweets @BUCollegeofENG
Congrats 🎉 the BU Technology Development's 2023 Ignition Awards have been given to 8️⃣ research projects, each recognized for its commercial potential. Among the 2023 winners are a tooth-saving formula, AI-powered reading tool, and others. Learn more. ➡️ bu.edu/articles/2023/…
Congrats 🎉 the BU Technology Development's 2023 Ignition Awards have been given to 8️⃣ research projects, each recognized for its commercial potential. Among the 2023 winners are a tooth-saving formula, AI-powered reading tool, and others. Learn more. ➡️ spr.ly/6006PCx66
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New pub on #digitalmeasures of gait related with worsening pain and function in knee osteoarthritis identified using ensemble #MachineLearning in a large cohort. Led by Dr. Kathryn Bacon @BU_BMC_Rheum …nlinelibrary-wiley-com.ezproxy.bu.edu/doi/10.1002/ac… #digitalhealth #wearables #chronicpain @BUSargent
@vkola_lab @BUMedicine @BU_CDS @BUCompSci @BU_CBM @NIHAging Congratulations Kolachalama..
I am thrilled to have been part of this study and want to congratulate all of the authors on this work!
Our latest study in @SkeletalRadiol explores how subchondral bone length, a novel #MRI-derived measure, can predict the need for total #knee replacement due to #Osteoarthritis.🦵🔬 doi.org/10.1007/s00256… With @ProfDeepakKumar @TDCapellini @BUMedicine @BU_CDS @BUCompSci @BU_CBM
Our next speaker is our very own @vkola_lab talking about "Mining clinical and digital data for dementia assessment". WHEN: Monday, February 12th 12:00pm - 1:00 pm EST WHERE: 635 Commonwealth Ave, room# 236 OR on Zoom: bostonu.zoom.us/meeting/regist…
In a @BU_Tweets #HTAN supported study, @rushin_gindra, @vkola_lab, et al. developed a computational pipeline for whole-slide H&E images to differentiate between bronchial #premalignant lesions by progression status @biorxivpreprint biorxiv.org/content/10.110…. #LCSM
This study shows that collecting smartphone application data in an unsupervised, remote, and naturalistic setting in a large, community‐based population is feasible. #AHAJournals #JAHASpotlight @PSunderaraman @Ileana_DeAndaD @vkola_lab ahajrnls.org/3HppTnZ
@JAHA_AHA @PSunderaraman @ludyshihmd @vkola_lab So proud of the work our team has put together!
The future of patient monitoring is using passive data collection. But how do we get to that goal in our patients with #Alzheimer Disease? Find out in this #AHAJournals #JAHASpotlight #Review from @Ileana_DeAndaD @PSunderaraman @ludyshihmd @vkola_lab ahajrnls.org/3RVQSwc
Congratulations to Dr. Sus Waikar for his election to the American Society for Clinical Investigation! Dr. Salant (elected 1987) and Dr. Cohen (elected 2007) are other two members of our Section on the ASCI. beta.the-asci.org/news/annual-me…
Free to read: Large Language Models in Neurology Research and Future Practice bit.ly/3Gr3xC6 #NeuroTwitter #AI
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Join the #ResearchOnTap conversation about Health Data Science. Hear from @BUexperts on how #DataScience can shape #Healthcare practices, policies and our understanding of the world. Host: Debbie Cheng, @BUSPH Population Health Data Science Program ➡️ spr.ly/6013u0Sn1
Dr. Jennifer Beane and @vkola_lab et al. @BU_CBM #HTAN created a computational pipeline for bronchial #premalignant lesion stratification to identify those at risk of #LungCancer progression @biorxivpreprint biorxiv.org/content/10.110…. #LCAM #LCSM
Does your Machine Learning project require the creation of different classes of annotation on large biomedical images? See how PixelView lets you customize and color code annotations pixelview.deeppath.ai #MachineLearning #DigitalPathology
Comparison of multiple H&E images is a common requirement when generating annotations necessary for downstream machine learning. PixelView enables Web-based side-by-side image display for collaborative annotation. Free trial available at: pixelview.deeppath.ai
Thanks to BU Evans Center IBR, @BUDeptofMed, @OTDatBU, @BostonUResearch, @BU_CTSI for supporting our inaugural Biomedical Innovation Technologies Affinity Research Collaborative (BIT-ARC) to develop AI digital pathology diagnostic tool for kidney disease bumc.bu.edu/evanscenteribr…
New in @GreenJournal by first author Dr. Michael Romano of @UCSFimaging & colleagues from @BUMedicine, @BU_ece: Large Language Models in Neurology Research & Future Practice. n.neurology.org/content/early/…
LLMs put to good use!
Thrilled to see this online! With Mike Romano @UCSFimaging @RadsUcsf @ludyshihmd @YPaschalidis #LLM @BU_CBM @BUMedicine @BU_CDS @BUCompSci @BU_Tweets @BUCollegeofENG
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