Speaker Abstracts

Topic 1: AI to improve accuracy of diagnosis and health risk assessment

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanisław Jastrzębski et al.
Presented By: Krzysztof J. Geras

Topic 2: AI to improve selection of treatment options

Automated prognosis of prenatal hydronephrosis
Lauren Erdman, Marta Skreta, Mandy Rickard​, Carson McLean, Aziz Mezlini​, Anne-Sophie Blais​​, Michael Brudno et al.

Topic 3: AI to improve step-by-step clinical pathways used to apply treatments

Deep Learning pipeline for the automatic segmentation and 3D model generation of the four heart chambers; applied uses in pre-surgical planning
Alex Deakyne, MS

Guiding Heparin Treatment with Reinforcement Learning
Tony Duan, MS

Machine Learning-Assisted Prediction of Surgical Mortality of Lung Cancer Patients
Sidra Xu

Topic 4: AI to detect and correct failures in clinician, patient and lay care-giver treatment actions inside and outside of healthcare facilities

Reducing childhood blindness from retinopathy of prematurity using artificial intelligence
J Peter Campbell, MD, MPH

A Conversational Dialogue Agent to Improve Outcomes in Healthcare
Maksim Tsvetovat, PhD

Topic 5: Innovation in AI methods that increase AI’s capacity to improve healthcare

Noninvasive cellular imaging in live skin makes histopathology accessible for AI innovation
Gabriel Sanchez, PhD

Topic 6: AI to improve patients’ ability to self-assess symptoms, select and implement self-care options to avoid use of or more successfully partner with health care professionals

Tuning semantic consistency of active medical diagnosis: a walk on the semantic simplex
Albert Buchard, Adam Baker, Konstantinos Gourgoulias, Alexandre Navarro, Yura Perov, Max Zwiessele, and Saurabh Johri

Contextual Normalcy: a participatory artificial intelligence research project on creating community-driven mental health classifications and diagnoses
Christine Meinders, MFA, MA

A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis
Salman Razzaki, Adam Baker, Yura Perov, Katherine Middleton, Janie Baxter, Daniel Mullarkey, Davinder Sangar et al.
Presented by: Saurabh Johri

Poster Abstracts

Rapid Automated Cardiac Imaging 
A. De Goyeneche, N.O. Addy1 H. Islam, E. Peterson, W.R. Overall, J.M. Santos, B.S. Hu

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning 
Anis Davoudi, Kumar Rohit Malhotra, Benjamin Shickel, Scott Siegel, Seth Williams, Matthew Ruppert, Emel Bihorac et al.

AI-Assisted Thyroid Malignancy Prediction From Whole-Slide Images
David Dov∗, Shahar Z. Kovalsky†, Jonathan Cohen‡, Danielle Elliott Range§, Ricardo Henao*, Lawrence Carin*

Predicting Blood Pressure Response to Fluids Bolus Therapy Using Attention-Based Neural Networks for Clinical Interpretability
Uma Girkar, Ryo Uchimido, Li-wei H Lehman, Peter Szolovits, Leo Celi, Wei-Hung Weng

Facilitating the Adoption of Reflectance Confocal Microscopy (RCM) in Clinical Cancer Care Practice with Machine Learning
Kivanc Kose, Alican Bozkurt, Christi Alessi-Fox, Melissa Gill, Dana H. Brooks, Jennifer G. Dy, Milind Rajadhyaksha

Automatic Hip Fracture Identification and Functional Subclassification with Deep Learning
Justin D Krogue MD*, Kaiyang Cheng (Victor), Kevin M Hwang MD, Paul Toogood MD, Eric G Meinberg MD, Erik J Geiger MD, Musa Zaid MD, et al.

MobileClinic: An end-to-end software architecture for analyzing human movement on a mobile device
Sreehari Rammohan, Łukasz Kidzinski, Scott Delp

DeepSOFA: Clinical Deep Learning for Real-Time Acuity Assessments of Critically Ill ICU Patients
Benjamin Shickel, Tyler Loftus, Lasith Adhikari, Tezcan Ozrazgat-Baslanti, Azra Bihorac, Parisa Rashidi

Diagnostic Screening of Cognitive Status with Dialogue Agent
Fengyi Tang​​, Ikechukwu Uchendu, Fei Wang​, Hiroko H. Dodge, ​Jiayu Zhou

Ada Health: AI-powered Symptom Assessment Platform leads to improved patient experience, improved care outcomes, and clinician efficiencies
Dr. Vishaal Virani and Dr. Stephen Miller

Alzheimer's Behavior-learning Cognitive System
Ying Wang

Quantification of Donor Liver Steatosis Using a Computer Imaging Platform
Linfeng Yang*, Raja R Narayan*, Simon Chen, Charles Hsu, Natasha Abadilla, John Higgins, Marc L. Melcher

Early Screening for Children with Fetal Alcohol Spectrum Disorder via Natural Viewing Behavior
Chen Zhang, James Reynolds, Douglas P. Munoz, Laurent Itti

Questions? Email sskelly@stanford.edu for more information.