Our Speakers

20220223 - mgb x mit bg no shadow (1).png
20220228 - mgb x mit logo.png

AI Cures Conference

April 25th, 2022
Samberg Center, MIT

Posters

Note: Posters are sorted in alphabetical order of the title.

Poster ID

1

A Computational Approach to Cognitive Disease Diagnosis Through Delayed Recall Performance

Evan Kim, Randall Davis, Dana Penney

2

A Cross-Modal Autoencoder Framework Learns Holistic Representations of Cardiovascular State

Adityanarayanan Radhakrishnan, Sam Freesun Friedman, Shaan Khurshid, Kenney Ng, Puneet Batra, Steven Lubitz, Anthony Philippakis, Caroline Uhler

3

A Deep Autoencoder Model to Denoise Visual Fields in Glaucoma

Vishal Sharma, Lucy Shen, Tobias Elze, Min Shi, Louis Pasquale, Mengyu Wang

4

A machine learning toolbox for breast oncology patients to better understand their clinical notes

Mercy N Asiedu, Irbaz Riaz, Niklas Mannhardt, Daniel Ajayi, Katie Liu, Alejandro Buendia, David Sontag

5

A smart compression sleeve for lymphedema treatment

Joseph DelPreto, Elizabeth Hausman, Brooke Juhel, Amanda Jung, Cheryl Brunelle, Alphonse Taghian, Daniela Rus

6

Affective Medical Estimation and Decision Making via Visualized Machine Learning

Mohammad Eslami, Solale Tabarestani, Ehsan Adeli, Glyn Elwyn, Tobias Elze, Nazlee Zebardast, Nassir Navab, Malek Adjouadi

7

AI-informed real-time speech prosthesis for neurological voice and speech disorders

Stefan K. Ehrlich, Kristina Simonyan

8

An AI system to diagnose ischemic heart disease from reduced-lead electrocardiogram data

Hui Ren, Qiong Zhou Huang, Jeongwan Koh, Dufan Wu, Quanzheng Li, Dimitrios Pantazis

9

An Artificial Intelligence (AI) Model for Screening Computed Tomography (CT) Imaging for Thyroid Eye Disease and Optic Neuropathy

Soomin Jeon, Paul Zhou, Lisa Y. Lin, Jonathan Lu, Synho Do, Nahyoung Grace Lee

10

An Artificial Intelligence-based Surgical Guardian System

Yutong Ban, Jennifer A. Eckhoff, Guy Rosman, Daniel A. Hashimoto, Ozanan Meireles and Daniela Rus

11

Artificial Intelligence Detects Parkinson’s Disease and its Severity from Nocturnal Breathing

Yuzhe Yang, Yuan Yuan, Guo Zhang, Hao Wang, Ying-Cong Chen, Yingcheng Liu, Christopher G. Tarolli, Daniel Crepeau, Jan Bukartyk, Mithri R. Junna, Aleksandar Videnovic, Terry D. Ellis, Melissa C. Lipford, Ray Dorsey, Dina Katabi

12

Assessing Parkinson’s Disease at Home: Contactless Monitoring of Disease Severity, Progression, and Medication Response Using Radio Signals

Yingcheng Liu, Guo Zhang, Christopher G. Tarolli, Rumen Hristov, Stella Jensen-Roberts, Emma M. Waddell, Taylor L. Myers, Meghan E. Pawlik, Julia M. Soto, Renee M. Wilson, Yuzhe Yang, Timothy Nordahl, Karlo J. Lizarraga, Jamie L. Adams, Ruth B. Schneider, Karl Kieburtz, Terry Ellis, Ray Dorsey, Dina Katabi

13

Augmenting existing deterioration indices with chest radiographs to predict clinical deterioration

Emily Mu, BSE, MEng; Sarah Jabbour, BSE, BBA; Adrian V. Dalca, PhD; John Guttag, PhD; Jenna Wiens, PhD; Michael W. Sjoding, MD, MSc

14

Automated Segmentation of Sacral Chordomas and Surrounding Muscles Using Deep Learning Ensemble

Léonard Boussioux*, Yu Ma*, Nancy Thomas, Dimitris Bertsimas, Yen-Lin Chen, Nadya Shusharina, Jennifer Pursley, Thomas DeLaney, Jack Qian, Thomas Bortfeld

15

Biologically Interpretable Representation Learning Algorithms for Characterizing and Predicting Cancer Immunotherapy Resistance

Ifrah Tariq, Bracha Laufer-Goldshtein, Ernest Fraenkel

16

Calibrated Selective Prediction

Adam Fisch, Tommi Jaakkola, Regina Barzilay

17

Capturing Brain Disease Mechanisms within Genetic and Environmental Diversity

Philippe Habets, Aarti Jajoo, Constantinos Daskalakis, Nikolaos Daskalakis

18

Clustering Interval-Censored Time-Series for Disease Phenotyping

Irene Y. Chen, Rahul G. Krishnan, David Sontag

19

Computational approaches to identify ALS disease signatures from multi-omic data in a heterogeneous patient population

Stanislav Tsitkov*, Velina Kozareva*, Answer ALS Consortium, Ernest Fraenkel

20

Computer Software Modeling of Biomechanical Stress – Detailed Analysis of The Spine/ Hip Complex

Zacharia Isaac MD, David Binder MD, Danielle Sarno MD, Jay Zampini MD

21

Decoding speech from human motor cortex using an intracortical brain computer interface

Daniel B. Rubin, Tommy Hosman, Anastasia Kapitonava, Ziv M. Williams, John D. Simeral, Sydney S. Cash, Leigh R. Hochberg

22

Deep learning for identifying new synergistic drug combinations

Wengong Jin, Jonathan M Stokes, Richard T Eastman, Zina Itkin, Alexey V Zakharov, James J Collins, Tommi S Jaakkola, Regina Barzilay

23

Deep learning MRI-based model for prediction of clinically significant prostate cancer

Keyan Salari, Harrison Le, Janice Yang, Peter Mikhael, Mukesh Harisinghani, Regina Barzilay

24

Deep learning to evaluate metabolic risk in people with HIV

Jen Manne-Goehler, Tzu-Ming Harry Hsu, Peter Szolovits, Alex Goehler, Janet Lo

25

Detecting Overwriting in Handwritten Digits

Angela Li, Randall Davis, Dana Penney

26

Detecting the Effects of Proxies on Bias in Clinical Algorithms

Vinith M. Suriyakumar, Marzyeh Ghassemi

27

Detection of OOD Clinical Notes with Local Manifold Smoothness

Nathan Ng, Neha Hulkund, Marzyeh Ghassemi

28

Endomicroscopy with AI and physics-assisted design

Li-Yu Yu, Sixian You

29

Enhancing patients’ care using routinely collected single cell blood data: learning a joint distribution from marginals

Veronica Tozzo; John Higgins

30

EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction

Hannes Stärk*, Octavian Ganea*, Lagnajit Pattanaik, Regina Barzilay, Tommi Jaakkola

31

Evaluating Machine Learning for “Loophole” Detection and Decisions in Healthcare Settings

Aparna Balagopalan, Tom Hartvigsen, Marzyeh Ghassemi

32

Evolution Prediction by Deep Generative Model

Wenxian Shi, Ryan Tso, Jonathan Stokes, and Regina Barzilay

33

Fair Organ Allocation

Hammaad Adam, Rene Bermea, Mingying Yang, Leo Celi, Marzyeh Ghassemi

34

Falsification before Extrapolation in Causal Effect Estimation

Ming-Chieh Shih, Mike Oberst, Zeshan Hussein

35

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance

Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leora Horwitz, David Sontag

36

Generation of protein structures with deep learning

Jason Yim, Brian Trippe, Doug Tischer

37

Graphene-Lined Porous Gelatin Glycidyl Methacrylate Hydrogels: Implications for Tissue Engineering

Sina Sharifi, Hannah Sharifi, Ali Akbari, Claes H Dohlman, Eleftherios I Paschalis, Miguel Gonzalez-Andrades, Jing Kong, James Chodosh

38

High Fidelity Medical Image-to-Image Translation with Spatial-Intensity Transforms

Clinton J. Wang, Natalia S. Rost, Polina Golland

39

Hyperbolic graph embedding of magnetoencephalography brain networks to study brain alterations in patients with subjective cognitive decline.

Cole Baker, Isabel Suarez-Mendez, Fernando Maestu, Dimitrios Pantazis, Mengjia Xu

40

iBOCA: iPad App for Cognitive Testing

Kalyan Veeramachaneni, Seth Amarasinghe, Sana Chowdhry, Alexandra Zytek, Frances Hartwell

41

Identifying Metabolite Spectral Patterns that Reflect Outcome after Cardiac Arrest Using Machine Learning

Marcia Sahaya Louis, Jong Woo Lee, Huijun Vicky Liao, Ajay Joshi , Rohit Singh , Alexander Lin

42

ImageOmicsNet: Linking Imaging with Genomics through Machine Learning

Koseki J. Kobayashi-Kirschvink, Charles S. Comiter, Aviv Regev, Jian Shu

43

Improving the Fairness of Chest X-ray Classifiers

Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Robert Pfohl, Marzyeh Ghassemi

44

Inadventent Multimodal Signals As Indicators of Cognitive Health

Dana Penney, Randall Davis

45

Inferring pulmonary capillary wedge pressure from minimally invasive measurements

Aniruddh Raghu, Daphne Schlesinger, Eugene Pomerantsev, John Guttag, Collin Stultz

46

Influence of auditory brainstem implant (ABI) position on perception: a multi-center study

Alejandro Garcia, MD; Sonja Poe; Afash Haleem; Victor Adenis, PhD; M. Christian Brown, PhD; Barbara S. Hermann, PhD; Daniel J. Lee, MD, FACS

47

Integrated multimodal artificial intelligence framework for healthcare applications

Luis R. Soenksen, Yu Ma, Cynthia Zeng, Leonard D.J. Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael L. Li, Ignacio Fuentes, Dimitris Bertsimas

48

Integration of Spatial Transcriptomics with Chromatin Images Using Graph-Based Autoencoder Identifies Joint Biomarkers for Alzheimer’s Disease

Xinyi Zhang, Xiao Wang, GV Shivashankar, Caroline Uhler

49

Learning Dynamic Treatment Regimes from Observational Health Data

Li-wei Lehman, Zach Shahn

50

Learning from Multiple Noisy Labels: Ovulation Prediction from Menstrual Cycles

Divya Shanmugam, John Guttag

51

Learning geometric motifs for fast protein-ligand screening

Menghua Wu, Wengong Jin, Regina Barzilay, Tommi Jaakkola

52

Learning-based high-speed programmable light source for label-free in vivo imaging

Tong Qiu, Artem Gazizov, Sixian You

53

Leveraging serial MRI radiomics and machine learning to stratify risk of radiation necrosis in patients with brain metastases managed with stereotactic radiation and immunotherapy

Hesham Elhalawani, Lubna Hammoudeh, Daphne Haas-Kogan, Ayal Aizer

54

Leveraging Time-Irreversibility With Order-Contrastive Pretraining

Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David Sontag

55

Local Explanations for Clinical Risk Scores

Yuria Utsumi, Hussein Mozannar, Irene Chen, David Sontag

56

Machine Learning Delivers an Objective, Sensitive, and Accurate Measure of Itch and its Impact on Sleep

Michail Ouroutzoglou, Mingmin Zhao, Hariharan Rahul, Asima Badic, Brian Kim, Dina Katabi

57

Machine Learning Driven User Interfaces for Electronic Health Records

Monica Agrawal, Luke Murray, Divya Gopinath, Steven Horng, David Karger, David Sontag

58

Machine Learning Tools for Analyzing the Development of Cellular-scale Neuronal Networks in Health and Disease

Susanna B. Mierau, Erik Hemberg, Una-May O'Reilly

59

ML-driven antimicrobial stewardship for uncomplicated urinary tract infection

Sanjat Kanjilal, Michael Oberst, Sooraj Boominathan, Helen Zhou, David C Hooper, David Sontag

60

Multi-Task Partially Convolutional Networks for Artifacts Imputation in Retinal Nerve Fiber Layer Thickness Maps

Min Shi, Lucy Shen, Tobias Elze, Vishal Sharma, Louis Pasquale, Mengyu Wang

61

Multimodal Artificial Intelligence for Chest Pathology Diagnosis

Luis R. Soenksen*, Yu Ma*, Cynthia Zeng*, Léonard Boussioux*, Kimberly Villalobos Carballo*, Liangyuan Na*, Holly M. Wiberg, Michael L. Li, Ignacio Fuentes, Dimitris Bertsimas

62

Multimodal Learning of Prognostic Biomarkers in Sepsis

Wei Liao, Ching-Yun Ko, Tsui-Wei Weng, Luca Daniel, Joel Voldman

63

Neural Pharmacodynamic State Space Modeling

Zeshan Hussain, Rahul G. Krishnan, David Sontag

64

omop-learn: An open-source library for deep contextual clinical prediction on longitudinal medical data

Alejandro Buendia, Hunter Lang, Neil Dixit, Rohan Kodialam, Rebecca Boiarsky, Justin Lim, Aditya Sai, David Sontag

65

Online Patient Operational Characteristics Predictions with Integrated Multimodal Machine Learning Frameworks

Luis R. Soenksen, Yu Ma, Cynthia Zeng, Leonard D.J. Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael L. Li, Ignacio Fuentes, Dimitris Bertsimas, Ali Haddad-Sisakht, Kyle Maulden, Yi Wang, Yiwen Zhang, Barry Stein, Daniel Kombert, Andrew Castiglione, Melissa Boisjoli-Langlois, Maram Khalifa, Pooja Hebbal

66

Optimizing Mental Healthcare for Older Adults: The Technology and Aging Lab at McLean Hospital

Hailey Cray M.P.H., Rebecca Dickinson B.S. B.A., Ipsit Vahia M.D.

67

Predicting clinical outcomes associated with Sepsis to inform resource allocation in the ICU

Angela Lin, Omar Skali Lami, Dessislava Pachamanova, Georgia Perakis, Lien Hong Le

68

Predicting Future Lung Cancer Risk with Low-dose Chest Computed Tomography

Peter G. Mikhael, Jeremy Wohlwend, Adam Yala, Justin Xiang, Angel K. Takigami, Patrick P. Bourgouin, PuiYee Chan, Sofiane Mrah, Lecia V. Sequist, Florian J. Fintelmann, Regina Barzilay

69

Quantifying Common Support between Multiple Treatment Groups Using a Contrastive-VAE

Wangzhi Dai, Collin M. Stultz

70

Quantifying Inequality in Underreported Conditions

Divya Shanmugam, Emma Pierson

71

Real-Time Arrhythmia Detection in Intensive Care Unit Using a Hybrid Convolutional Neural Network Approach

Sandeep Chandra Bollepalli, Rahul K. Sevakula, Wan‐Tai M. Au‐Yeung, Mohamad B. Kassab, Faisal M. Merchant, George Bazoukis, Richard Boyer, Eric M. Isselbacher, Antonis A. Armoundas

72

RHCnet: A deep learning model for inferring elevated pulmonary capillary wedge pressures from the 12-lead electrocardiogram

Daphne E. Schlesinger, Nathaniel Diamant, Aniruddh Raghu, Erik Reinertsen, Katherine Young, Puneet Batra, Eugene Pomerantsev, and Collin M. Stultz

73

Sensor-Based Characterization of Depression Studies: A collaboration between the MIT Media Lab and MGH Depression Clinical and Research Program

Szymon Fedor, Rosalind W. Picard, Paola Pedrelli

74

Spurious Signal Correction in Medical Images with Disentangled Latent Space Generative Models

Qixuan Jin, Marzyeh Ghassemi

75

Studying RNA Binding Proteins with Machine Learning

Felix Faltings, Jon Henninger, Ozgur Oksuz, Michael Yaffe, Rick Young, Regina Barzilay, Tommi Jakkola

76

Syfer: Neural Obfuscation for Private Data Release

Adam Yala, Victor Quach, Homa Esfahanizadeh, Rafael G. L. D'Oliveira, Ken R. Duffy, Muriel Médard, Tommi S. Jaakkola, Regina Barzilay

77

T-cell Target Prediction Guiding Disease Detection and Monitoring

Nitan Shalon, Jeremy Wohlwend, Regina Barzilay

78

Teaching Humans When To Defer to a Classifier via Exemplars

Hussein Mozannar, Arvind Satyanarayan, David Sontag

79

Tensor Based Framework for the Analysis of Tumor Microenvironment

Neriman Tokcan, Vignesh Shanmugam,Caroline Uhler, Todd Golub

80

Torsional Diffusion for Molecular Conformer Generation

Gabriele Corso, Bowen Jing, Regina Barzilay, Tommi Jaakkola

81

Towards Development, Validation, and Clinical Translation of Automated Segmentation for Vestibular Schwannomas

Krish Suresh MD, Ryan Bartholomew MD, Bradley Welling, MD PhD, Matthew Crowson MD MPA MASc FRCSC

82

Uncovering the important acoustic features for detecting vocal fold paralysis with explainable machine learning

Daniel M. Low, Vishwanatha Rao, Gregory Randolph, Phillip C. Song*, Satrajit S. Ghosh*

83

Understanding and Addressing the Usability Challenges of Machine Learning In Child Welfare Decision Making

Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan, Warren Wang, Laure Berti-Equille, Kalyan Veeramachaneni

84

Using Machine Learning to Understand Proteomic Subtypes of Medulloblastoma

Maxwell P. Gold, Veronika Pister, Noel Park, David Ghasemi, Raul Saurez, Andrew Masteller, Tobias Ehrenberger, Kristian Pajtler, Jennifer Cotter, Jill Mesirov, Scott Pomeroy, Robert Wechsler-Reya, Michael Taylor, Shawn Davidson, Ernest Fraenkel

85

Utilizing Machine Learning for Risk Stratification of Intraductal Papillary Mucinous Neoplasms and associated cancer

Yasmin G. Hernandez-Barco, Avinash Kambadakone, Itamar Chinn, Ignacio Fuentes Ribas

86

Validating Clinical Dead-ends Across Multiple Sites

Taylor Killian, Marzyeh Ghassemi

87

Wireless Seismocardiography: Enabling Long-Term Non-Contact Cardiovascular Monitoring

Unsoo Ha, Sohrab Madani, Fadel Adib

88

Write it like you see it: Detectable differences in clinical notes by race lead to differential model recommendations

Hammaad Adam, Ming Ying Yang, Kenrick Cato, Charles Senteio, Marzyeh Ghassemi