Marina Sirota (@msirota84) 's Twitter Profile
Marina Sirota

@msirota84

Bioinformatician, data scientist, researcher

ID: 2869829804

calendar_today22-10-2014 00:57:14

936 Tweet

982 Followers

96 Following

Jonathan H Chen MD PhD (@jonc101x) 's Twitter Profile Photo

Human plus computer, when combined, will deliver better results than either? Now I'm unsure. I've taken on a Medical Education with AI role, because we need tech development and (re)training on how to use powerful new tools. abc7news.com/post/artificia…

University of California (@uofcalifornia) 's Twitter Profile Photo

Researchers at UC San Francisco have enabled a man who is paralyzed to control a robotic arm that receives signals from his brain via a computer 🦾 bit.ly/4iJZbHk

UC Joint Computational Precision Health Program (@ucjointcph) 's Twitter Profile Photo

.Irene Chen on combining data sources to ensure that AI models work fairly and well in all settings and for all patients—and also on a new work examining what patients want from LLMs and how they want the health system to use them. @ucsf AI research day. Berkeley Computing, Data Science, and Society

.<a href="/irenetrampoline/">Irene Chen</a> on combining data sources to ensure that AI models work fairly and well in all settings and for all patients—and also on a new work examining what patients want from LLMs and how they want the health system to use them. @ucsf AI research day. <a href="/BerkeleyCDSS/">Berkeley Computing, Data Science, and Society</a>
UC Joint Computational Precision Health Program (@ucjointcph) 's Twitter Profile Photo

.Maya Petersen on training a large clinical behavioral—rather than large language model— to predict clinical action likely to come next in time and using causal inference to optimize outcomes. More methods pioneering discussed here at UCSF AI research day. Jon Kolstad

.<a href="/DrMayaPetersen/">Maya Petersen</a> on training a large clinical behavioral—rather than large language model— to predict clinical action likely to come next in time and using causal inference  to optimize outcomes.  More methods pioneering discussed here at UCSF AI research day. <a href="/jtkolstad/">Jon Kolstad</a>
Lorenzo Righetto (@lorenzorighett7) 's Twitter Profile Photo

An AI model defines a data-driven set of Total Parenteral Nutrition compositions to assist clinicians in personalized treatment of neonates in intensive care, with validation from external cohorts and a blinded reader study Nima Aghaeepour Marina Sirota nature.com/articles/s4159…

tomiko oskotsky (@tomiko22) 's Twitter Profile Photo

Thrilled about our collaborative work with the wonderful team at Stanford led by Joe and Nima Aghaeepour, showing how AI-guided personalized TPN treatments can lead to improved outcomes for neonates in the critical care setting. Marina Sirota UCSF Bakar Computational Health Sciences Institute March of Dimes

Stanford Neonatology (@stanfordneo) 's Twitter Profile Photo

med.stanford.edu/news/all-news/… Using information from tens of thousands of nutrition prescriptions for preemies, AI identifies 15 distinct total parenteral nutrition (TPN) formulas that may reduce costs and medical errors and improve infant health. The study in Nature Medicine is by

Marina Sirota (@msirota84) 's Twitter Profile Photo

Yesterday marked my 10 year anniversary at UC San Francisco. What a decade - dozens of grants, 150+ papers and 50+ alumni. I'm incredibly thankful to all my colleagues as well as my team. Special thanks Atul Butte for his mentorship and support throughout my career! UCSF Bakar Computational Health Sciences Institute Sirota Lab at UCSF

Yesterday marked my 10 year anniversary at <a href="/UCSF/">UC San Francisco</a>. What a decade - dozens of grants, 150+ papers and 50+ alumni. I'm incredibly thankful to all my colleagues as well as my team. Special thanks <a href="/atulbutte/">Atul Butte</a> for his mentorship and support throughout my career! <a href="/UCSF_BCHSI/">UCSF Bakar Computational Health Sciences Institute</a> <a href="/SirotaLab/">Sirota Lab at UCSF</a>
Nicholas Tatonetti (@proftatonetti) 's Twitter Profile Photo

Our OnSIDES db -- the worlds most up-to-date resource of drug side effects is published at Med by Cell Press For all your drug safety analysis and prediction needs. OnSIDES is the first resource to combine US, UK, EU, and Japanese data all in one place. cell.com/med/abstract/S…

UC San Francisco (@ucsf) 's Twitter Profile Photo

UCSF’s first Research AI Day brought together 300+ people to explore how AI is reshaping discovery, care and population health, sparking new ideas across our research community. UCSF Bakar Computational Health Sciences Institute UCSF Epidemiology & Biostatistics

UCSF’s first Research AI Day brought together 300+ people to explore how AI is reshaping discovery, care and population health, sparking new ideas across our research community. <a href="/UCSF_BCHSI/">UCSF Bakar Computational Health Sciences Institute</a> <a href="/UCSF_Epibiostat/">UCSF Epidemiology & Biostatistics</a>
tomiko oskotsky (@tomiko22) 's Twitter Profile Photo

A privilege for our UC San Francisco team - Marina Sirota Marina Sirota, Roberta Keller, Boris Oskotsky Boris Oskotsky, Jean Costello, Jackie Roger - to work with the Stanford University team, led by Joe Phongpreecha & Nima Aghaeepour Nima Aghaeepour, exploring AI-guided TPN formulations for infants