The AI for Healthcare Bootcamp provides Stanford students an opportunity to do cutting-edge research at the intersection of AI and healthcare. Over two quarters, students receive training from PhD students and faculty in the medical school to work on high-impact research problems in small interdisciplinary teams.

Projects out of the bootcamp have included work in (1) radiology on automated diagnosis of diseases from x-rays, ultrasound, CT and MR, (2) pathology on automated detection of rare tumor subtypes and on time-consuming pathology tasks, (3) public health on prediction of patient costs and heterogeneous treatment effect estimation, and (4) mental health on prediction of treatment outcomes in depression.

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Teaching Team

Pranav Rajpurkar

PhD Student

Anand Avati

PhD Student

Jeremy Irvin

MS Student

Sharon Zhou

PhD Student

Andrew Ng

Professor

Nigam Shah

Professor

Matt Lungren

Professor

Curt Langlotz

Professor

Jeanne Shen

Professor

Sanjay Basu

Professor

Bhavik Patel

Professor

Kristen Yeom

Professor

Leanne Williams

Professor

Applications

Students with a background in artificial intelligence, software engineering or medicine are encouraged to apply. The applications for the spring+summer bootcamp are now open.

  • Early Applications due Mar 1st, 2019 at 11:59p PST.
  • Regular Applications due Apr 1st, 2019 at 11:59p PST.
  • Late Applications due Apr 7th, 2019 at 11:59p PST. Apply early to give yourself enough time to prepare for the interview.
  • Rolling interviews and selections until Apr 8th, 2019.
  • Bootcamp starts Apr 8th, 2019. Students can choose to pursue their second quarter of the bootcamp over the summer or over the fall.

AI Specialization

This role is suited for students who have taken machine learning and software engineering courses. Students will be able to apply and sharpen these skills, developing machine learning solutions to challenging problems with the mentorship of CS PhD students and in collaboration with medical school faculty. Students have the opportunity to take a deep dive into healthcare and co-author a research paper. We expect students to have:

  • Taken machine learning courses (CS229/CS230/CS224N/CS231N or equivalent).
  • Proficiency in software engineering (CS107 or equivalent), and have done Python programming.
  • The bootcamp as their primary academic engagement (20-30 hours per week in lab) outside of 1 or 2 courses. We encourage students to sign up for research credits (CS 199, CS 399 etc).

Medicine Specialization

This role is suited for students in the medical school. Students will work to define the focus of projects by exploring previous work and clinical utility. Students have the opportunity to work closely with the medical school faculty, take a deep dive into AI, and co-author a research paper. We expect students to:

  • Have medical knowledge / clinical experience (candidates have taken step 1 and/or completed at least some clinical rotations).
  • Know deep learning and machine learning at a conceptual level.
  • Dedicate 10-20 hours per week and attend 2 research meetings per week. Students can sign up for research credits (MED 199, MED 399 etc).

Deployment Specialization

AI projects are not complete before their tangible impact is demonstrated in the real world. This is why usable and robust deployment is a key element of our research projects.

This role is suited for students who have taken human computer interaction and software development courses. Students will be able to apply and sharpen these skills, developing solutions to challenging problems at the intersection of AI and healthcare with the mentorship of CS PhD students, medical school faculty and software industry experts. Students have the opportunity to take a deep dive into healthcare and co-author a research paper. We expect students to have:

  • Proficiency in Python, Linux, Cloud Computing and JavaScript
  • Have taken one or more of CS140, CS142, CS147, CS 193A, CS194H, CS210, or CS247
  • The bootcamp as their primary academic engagement (20-30 hours per week in lab) outside of 1 or 2 courses. We encourage students to sign up for research credits (CS 199, CS 399 etc).

Past Bootcamp Cohorts

Winter 2018-2019

Anuj Pareek

Med Student

Chris Wang

BS Student

Jingbo Yang

BS Student

Mark Sabini

BS Student

Minh Phu

BS Student

Nathan Dass

MS Student

Fall 2018-2019

Alex Wang

BS Student

Amirhossein Kiani

MS Student

Amit Schechter

BS Student

Andrew Kondrich

BS Student

Bora Uyumazturk

BS Student

Chloe O'Connell

Med Student

Jason Li

BS Student

Nishit Asnani

MS Student

Rebecca Gao

Med Student

Soumya Patro

MS Student

Spring 2017-2018

Behzad Haghgoo

BS Student

Ben Cohen-Wang

BS Student

Chris Chute

MS Student

Joe Lou

BS Student

Kelly Shen

MS Student

Meng Zhang

MS Student

Michael Ko

BS Student

Nidhi Manoj

BS Student

Philip Hwang

BS Student

Robin Cheong

BS Student

Silviana Ciurea Ilcus

MS Student

Yifan Yu

MS Student

Winter 2017-2018

Allison Park

MS Student

Andrew Huang

BS Student

Atli Kosson

MS Student

Chris Lin

MS Student

Erik Jones

BS Student

Henrik Marklund

MS Student

Jessica Wetstone

MS Student

Matthew Sun

BS Student

Michael Bereket

BS Student

Nicholas Bien

BS Student

Norah Borus

BS Student

Shubhang Desai

BS Student

Suvadip Paul

MS Student

Thao Nguyen

BS Student

Tanay Kothari

BS Student

Fall 2017-2018

Aarti Bagul

MS Student

Brandon Yang

BS Student

Daisy Ding

MS Student

Hershel Mehta

MS Student

Kaylie Zhu

BS Student

Tony Duan

MS Student

We invite you to join the AI revolution in healthcare

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