Program Highlights »
Fri Dec 8th 08:00 AM -- 06:30 PM @ 104 A
Machine Learning for Health (ML4H) - What Parts of Healthcare are Ripe for Disruption by Machine Learning Right Now?
Andrew Beam · Andrew Beam · Madalina Fiterau · Madalina Fiterau · Peter Schulam · Peter Schulam · Jason Fries · Jason Fries · Michael Hughes · Michael Hughes · Alex Wiltschko · Alex Wiltschko · Jasper Snoek · Jasper Snoek · Natalia Antropova · Natalia Antropova · Rajesh Ranganath · Rajesh Ranganath · Bruno Jedynak · Bruno Jedynak · Tristan Naumann · Tristan Naumann · Adrian Dalca · Adrian Dalca · Adrian Dalca · Adrian Dalca · Tim Althoff · Tim Althoff · SHUBHI ASTHANA · SHUBHI ASTHANA · Prateek Tandon · Prateek Tandon · Jaz Kandola · Jaz Kandola · Alexander Ratner · Alexander Ratner · David Kale · David Kale · Uri Shalit · Uri Shalit · Marzyeh Ghassemi · Marzyeh Ghassemi · Isaac S Kohane · Isaac S Kohane

Workshop Home Page

The goal of the NIPS 2017 Machine Learning for Health Workshop (ML4H) is to foster collaborations that meaningfully impact medicine by bringing together clinicians, health data experts, and machine learning researchers. We aim to build on the success of the last two NIPS ML4H workshops which were widely attended and helped form the foundations of a new research community.

This year’s program emphasizes identifying previously unidentified problems in healthcare that the machine learning community hasn't addressed, or seeing old challenges through a new lens. While healthcare and medicine are often touted as prime examples for disruption by AI and machine learning, there has been vanishingly little evidence of this disruption to date. To interested parties who are outside of the medical establishment (e.g. machine learning researchers), the healthcare system can appear byzantine and impenetrable, which results in a high barrier to entry. In this workshop, we hope to reduce this activation energy by bringing together leaders at the forefront of both machine learning and healthcare for a dialog on areas of medicine that have immediate opportunities for machine learning. Attendees at this workshop will quickly gain an understanding of the key problems that are unique to healthcare and how machine learning can be applied to addressed these challenges.

The workshop will feature invited talks from leading voices in both medicine and machine learning. A key part of our workshop is the clinician pitch; a short presentation of open clinical problems where data-driven solutions can make an immediate difference. This year’s program will also include spotlight presentations and two poster sessions highlighting novel research contributions at the intersection of machine learning and healthcare. The workshop will conclude with an interactive a panel discussion where all speakers respond to questions provided by the audience.

08:00 AM Welcome and opening remarks (Talk)
08:20 AM Keynote: Zak Kohane, Harvard DBMI (Talk)
Isaac S Kohane
08:55 AM Jennifer Chayes, Microsoft Research New England (Talk)
Jennifer Chayes
09:20 AM Keynote: Susan Murphy, U. Michigan (Talk)
Susan Murphy
09:55 AM Contributed spotlights (Spotlight)
10:20 AM Coffee break and Poster Session I (Poster Session)
Nishith Khandwala, Steve Gallant, Greg Way, Aniruddh Raghu, Li Shen, Aydan Gasimova, Alican Bozkurt, Willie Boag, Daniel Lopez-Martinez, Ulrich Bodenhofer, Samaneh Nasiri GhoshehBolagh, Michelle Guo, Christoph Kurz, Kirubin Pillay, Kimis Perros, George H Chen, Alexandre Yahi, Madhumita Sushil, Sanjay Purushotham, Elena Tutubalina, Tejpal Virdi, Marc-Andre Schulz, Samuel Weisenthal, Bharat Srikishan, Petar Veličković, Kartik Ahuja, Andrew Miller, Erin Craig, Disi Ji, Filip Dabek, Chloé Pou-Prom, Hejia Zhang, Janani Kalyanam, Wei-Hung Weng, Harish S. Bhat, Hugh Chen, Simon Kohl, Mingwu Gao, Tingting Zhu, Ming-Zher Poh, Iñigo Urteaga, Antoine Honoré, Alessandro De Palma, Maruan Al-Shedivat, Pranav Rajpurkar, Matthew McDermott, Vincent Chen, Yanan Sui, Yun-Geun Lee, Li-Fang Cheng, David Fang, Sibt Hussain, Cesare Furlanello, Zeev Waks, Hiba Chougrad, Hedvig Kjellstrom, Finale Doshi-Velez, Wolfgang Fruehwirt, Yanqing Zhang, Lily Hu, Junfang Chen, Sunho Park, Gatis Mikelsons, Jumana Dakka, Stephanie Hyland, yann chevaleyre, Hyunwoo Lee, Xavier Giro-i-Nieto, David Kale, Michael Hughes, Gabriel Erion, Rishab Mehra, William Zame, Stojan Trajanovski, Prithwish Chakraborty, Kelly Peterson, Muktabh Srivastava, Amy Jin, Helio Tejeda Lemus, Priyadip Ray, Tamas Madl, Joseph Futoma, Enhao Gong, Syed Rameel Ahmad, Eric Lei, Ferdinand Legros
10:50 AM Invited clinical panel (Panel Discussion)
Enrique Velazquez, James Priest, irina strigo
11:50 AM Keynote II: Fei-Fei Li, Stanford (Talk)
Li Fei-Fei
01:30 PM Interactive panel (Panel Discussion)
02:30 PM Jill Mesirov, UCSD (Talk)
Jill Mesirov
02:55 PM Greg Corrado, Google (Talk)
Greg Corrado
03:20 PM Coffee break and Poster Session II (Poster Session)
Mohamed Kane, Albert Haque, Vagelis Papalexakis, John Guibas, Peter Li, Carlos Arias, Eric Nalisnick, Padhraic Smyth, Frank Rudzicz, Xia Zhu, Ted L Willke, Noemie Elhadad, hansisnow Raffauf, hsuresh Suresh, Paroma Varma, Yisong Yue, Oggi Rudovic, Evidation Foschini, Syed Rameel Ahmad, Hasham ul Haq, Valerio Maggio, Giuseppe Jurman, Sonali Parbhoo, Pouya Bashivan, Jyoti Islam, Mirco Musolesi, Chris Wu, Alexander Ratner, Jared Dunnmon, Cristóbal Esteban, Aram Galstyan, Greg Ver Steeg, Hrant Khachatrian, Marc Górriz, Mihaela van der Schaar, Anton Nemchenko, Manasi Patwardhan, Tanay Tandon
03:50 PM Award session + A word from our affiliates (Award Session)
04:10 PM Mihaela Van Der Schaar, Oxford (Talk)
04:35 PM Networking Break (Break)
05:00 PM Jure Leskovec, Stanford (Talk)
Jure Leskovec
05:25 PM Keynote: Atul Butte (Talk)
Atul Butte
06:00 PM Closing Remarks (Talk)