Russ Altman

Russ Altman is the Kenneth Fong Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and (by courtesy) Computer Science at Stanford University. His primary research interests are in the application of computing to problems relevant to medicine. Kim Branson is a senior vice president and Global Head of Artificial Intelligence and Machine Learning at GSK, where he leads the GSK.ai team, a group of nearly 100 machine learning researchers and engineers who are pioneering the application of AI to drug discovery and development. In this conversation with Stanford adjunct lecturer and STVP Director of Principled Entrepreneurship Jack Fuchs, Altman and Branson discuss how ethics and principles can shape innovation at the intersection of AI and drug development.  --------------------Stanford eCorner content is produced by the Stanford Technology Ventures Program. At STVP, we empower aspiring entrepreneurs to become global citizens who create and scale responsible innovations.CONNECT WITH USTwitter: https://twitter.com/ECorner LinkedIn: https://www.linkedin.com/company/stanfordtechnologyventuresprogram/ Facebook: https://www.facebook.com/StanfordTechnologyVenturesProgram/ YouTube: https://www.youtube.com/user/ecorner LEARN MOREeCorner Website: https://ecorner.stanford.edu/STVP Website: https://stvp.stanford.edu/Support our mission of providing students and educators around the world with free access to Stanford University's network of entrepreneurial thought leaders: https://ecorner.stanford.edu/give.

The Future of Everything with Russ Altman:"Russ Altman: Artificial intelligence takes on COVID-19"Days after COVID-19 broke out in the United States, Russ Altman and colleagues at Stanford's Institute for Human-Centered Artificial Intelligence (HAI) scrambled to organize a full-day online conference to replace the in-person meeting they were planning for spring 2020. Their topic: using AI to defeat the deadly new virus behind COVID-19 and, in particular, analyze how countries were responding; developing new ways of tracking and anticipating its spread; reshape the search for treatments and a vaccine; and, last but not least, to battling “infodemics” — the tendency for information overload to hinder scientific progress.With thousands from around the world tuning in for the live event and 60,000-plus views of the recordings since, the conference illustrated in real terms how an entire field pivoted in a matter of weeks to address the pandemic in new and promising ways. In this episode of Stanford Engineering's The Future of Everything, guest host Howard Wolf turns the tables on Altman — a medical doctor, an expert in bioinformatics and the HAI associate director who helped lead the conference — and digs deep on AI’s response to COVID-19.

Days after COVID-19 broke out in the United States, Russ Altman and colleagues at Stanford's Institute for Human-Centered Artificial Intelligence (HAI) scrambled to organize a full-day online conference to replace the in-person meeting they were planning for spring 2020. Their topic: using AI to defeat the deadly new virus behind COVID-19 and, in particular, analyze how countries were responding; developing new ways of tracking and anticipating its spread; reshape the search for treatments and a vaccine; and, last but not least, to battling “infodemics” — the tendency for information overload to hinder scientific progress. With thousands from around the world tuning in for the live event and 60,000-plus views of the recordings since, the conference illustrated in real terms how an entire field pivoted in a matter of weeks to address the pandemic in new and promising ways. In this episode of Stanford Engineering's The Future of Everything, guest host Howard Wolf turns the tables on Altman — a medical doctor, an expert in bioinformatics and the HAI associate director who helped lead the conference — and digs deep on AI’s response to COVID-19.

Wenn Sie zwei unterschiedliche Medikamente für verschiedene Zwecke verwenden, sollten Sie dies bedenken: Ihr Arzt könnte die Folgen des Mischens nicht völlig verstehen, weil die Wechselwirkungen von Arzneien sehr schwer zu untersuchen sind. In diesem faszinierenden und verständlichen Vortrag zeigt Russ Altman wie Ärzte unerwartete Arzneimittelwechselwirkungen anhand einer überraschenden Quelle erforschen: die Verlaufsprotokolle von Suchmaschinen.

Si vous prenez deux traitements différents pour deux raisons différentes, une réflexion s'impose : votre médecin peut ne pas complètement comprendre ce qui se passe quand les médicaments sont combinés, et ce parce que les interactions médicamenteuses sont incroyablement difficiles à étudier. Dans cet exposé fascinant et accessible, Russ Altman montre comment les médecins étudient les interactions médicamenteuses inattendues à l'aide d'une source surprenante : les requêtes sur les moteurs de recherche.

Se você toma dois medicamentos diferentes por duas razões diversas, aqui vai um pensamento perturbador: o seu médico talvez não saiba tudo o que acontece quando eles se combinam, porque é inacreditavelmente difícil estudar interações de remédios. Nesta palestra fascinante e acessível, Russ Altman mostra como médicos estão estudando interações medicamentosas inesperadas usando uma ferramenta surpreendente: históricos de pesquisa na Internet.

If you take two different medications for two different reasons, here's a sobering thought: your doctor may not fully understand what happens when they're combined, because drug interactions are incredibly hard to study. In this fascinating and accessible talk, Russ Altman shows how doctors are studying unexpected drug interactions using a surprising resource: search engine queries.

في حالة تناولت نوعين من الأدوية لمعالجة مرضين مختلفين، إليك هذه الحقيقة الواقعية: من المحتمل أن لا يفهم طبيبك ما يحدث تماما عند تناول هذين النوعين من الأدوية معا، لأنه من الصعب دراسة التفاعلات بين الأدوية. وخلال هذه المحاضرة الشيقة والمدهشة يبيّن روس ألتمان كيف يمكن للأطباء دراسة تفاعلات غير متوقعة بين الأدوية باستعمال آليات مدهشة: محركات البحث الاستفسارية.

Si toman dos medicamentos diferentes por dos razones diferentes, aquí hay un pensamiento aleccionador: El médico puede no entender completamente lo que sucede al combinarlos, ya que las interacciones entre medicamentos son muy difíciles de estudiar. En esta charla fascinante y accesible, Russ Altman muestra cómo los médicos están estudiando las interacciones inesperadas al combinar medicamentos y lo hacen mediante un recurso sorprendente: las consultas en los motores de búsqueda.

Guest:Russ Altman, Dept Chair, Bioengineering, Stanford University Bio and Contact Info Listen (5:32) A bioinformatician bottleneck? Listen (4:19) Does the engineer or coder have enough basic biology?