no code implementations • 6 May 2024 • Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, Eric Wang, Ellery Wulczyn, Fayaz Jamil, Theo Guidroz, Chuck Lau, Siyuan Qiao, Yun Liu, Akshay Goel, Kendall Park, Arnav Agharwal, Nick George, Yang Wang, Ryutaro Tanno, David G. T. Barrett, Wei-Hung Weng, S. Sara Mahdavi, Khaled Saab, Tao Tu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Jorge Cuadros, Gregory Sorensen, Yossi Matias, Katherine Chou, Greg Corrado, Joelle Barral, Shravya Shetty, David Fleet, S. M. Ali Eslami, Daniel Tse, Shruthi Prabhakara, Cory McLean, Dave Steiner, Rory Pilgrim, Christopher Kelly, Shekoofeh Azizi, Daniel Golden
Building upon Gemini's multimodal models, we develop several models within the new Med-Gemini family that inherit core capabilities of Gemini and are optimized for medical use via fine-tuning with 2D and 3D radiology, histopathology, ophthalmology, dermatology and genomic data.
no code implementations • 29 Apr 2024 • Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Ben Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale Webster, Joelle Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan
We evaluate Med-Gemini on 14 medical benchmarks, establishing new state-of-the-art (SoTA) performance on 10 of them, and surpass the GPT-4 model family on every benchmark where a direct comparison is viable, often by a wide margin.
no code implementations • 4 Mar 2024 • Sebastien Baur, Zaid Nabulsi, Wei-Hung Weng, Jake Garrison, Louis Blankemeier, Sam Fishman, Christina Chen, Sujay Kakarmath, Minyoi Maimbolwa, Nsala Sanjase, Brian Shuma, Yossi Matias, Greg S. Corrado, Shwetak Patel, Shravya Shetty, Shruthi Prabhakara, Monde Muyoyeta, Diego Ardila
Health acoustic sounds such as coughs and breaths are known to contain useful health signals with significant potential for monitoring health and disease, yet are underexplored in the medical machine learning community.
no code implementations • 11 Sep 2023 • Louis Blankemeier, Sebastien Baur, Wei-Hung Weng, Jake Garrison, Yossi Matias, Shruthi Prabhakara, Diego Ardila, Zaid Nabulsi
A crucial aspect of optimizing Slowfast NFNet for this application lies in identifying effective audio augmentations.
no code implementations • 2 Aug 2023 • Shawn Xu, Lin Yang, Christopher Kelly, Marcin Sieniek, Timo Kohlberger, Martin Ma, Wei-Hung Weng, Atilla Kiraly, Sahar Kazemzadeh, Zakkai Melamed, Jungyeon Park, Patricia Strachan, Yun Liu, Chuck Lau, Preeti Singh, Christina Chen, Mozziyar Etemadi, Sreenivasa Raju Kalidindi, Yossi Matias, Katherine Chou, Greg S. Corrado, Shravya Shetty, Daniel Tse, Shruthi Prabhakara, Daniel Golden, Rory Pilgrim, Krish Eswaran, Andrew Sellergren
In this work, we present an approach, which we call Embeddings for Language/Image-aligned X-Rays, or ELIXR, that leverages a language-aligned image encoder combined or grafted onto a fixed LLM, PaLM 2, to perform a broad range of chest X-ray tasks.
no code implementations • 9 May 2023 • Wei-Hung Weng, Sebastien Baur, Mayank Daswani, Christina Chen, Lauren Harrell, Sujay Kakarmath, Mariam Jabara, Babak Behsaz, Cory Y. McLean, Yossi Matias, Greg S. Corrado, Shravya Shetty, Shruthi Prabhakara, Yun Liu, Goodarz Danaei, Diego Ardila
We compared the DLS with the office-based refit-WHO score, which adopts the shared predictors from WHO and Globorisk scores (age, sex, smoking status, height, weight and systolic blood pressure) but refitted on the UK Biobank (UKB) cohort.
no code implementations • 5 Dec 2021 • Di Jin, Elena Sergeeva, Wei-Hung Weng, Geeticka Chauhan, Peter Szolovits
In this review, we focus on the interpretability of the DL models in healthcare.
1 code implementation • ICCV 2021 • Richard J. Chen, Ming Y. Lu, Wei-Hung Weng, Tiffany Y. Chen, Drew F.K. Williamson, Trevor Manz, Maha Shady, Faisal Mahmood
Survival outcome prediction is a challenging weakly-supervised and ordinal regression task in computational pathology that involves modeling complex interactions within the tumor microenvironment in gigapixel whole slide images (WSIs).
no code implementations • 9 Oct 2020 • Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan, Gamaleldin F. Elsayed, YuAn Liu
Class imbalance is a common problem in medical diagnosis, causing a standard classifier to be biased towards the common classes and perform poorly on the rare classes.
3 code implementations • 28 Sep 2020 • Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, Peter Szolovits
Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community.
1 code implementation • 26 Jun 2020 • Matthew B. A. McDermott, Tzu Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
CheXpert is very useful, but is relatively computationally slow, especially when integrated with end-to-end neural pipelines, is non-differentiable so can't be used in any applications that require gradients to flow through the labeler, and does not yield probabilistic outputs, which limits our ability to improve the quality of the silver labeler through techniques such as active learning.
2 code implementations • WS 2020 • Bhanu Pratap Singh Rawat, Wei-Hung Weng, So Yeon Min, Preethi Raghavan, Peter Szolovits
We explore state-of-the-art neural models for question answering on electronic medical records and improve their ability to generalize better on previously unseen (paraphrased) questions at test time.
no code implementations • 20 Mar 2020 • Szu-Yeu Hu, Shuhang Wang, Wei-Hung Weng, JingChao Wang, XiaoHong Wang, Arinc Ozturk, Qian Li, Viksit Kumar, Anthony E. Samir
Modern deep learning algorithms geared towards clinical adaption rely on a significant amount of high fidelity labeled data.
1 code implementation • 29 Feb 2020 • Wei-Hung Weng, Yu-An Chung, Schrasing Tong
In the era of clinical information explosion, a good strategy for clinical text summarization is helpful to improve the clinical workflow.
1 code implementation • NeurIPS 2019 • Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Dr.Mohammad Alizadeh
We present Park, a platform for researchers to experiment with Reinforcement Learning (RL) for computer systems.
no code implementations • 31 Oct 2019 • Ruibin Ma, Po-Hsuan Cameron Chen, Gang Li, Wei-Hung Weng, Angela Lin, Krishna Gadepalli, Yuannan Cai
However, manual classification for a huge number of reports on multiple tasks is labor-intensive.
no code implementations • 19 Sep 2019 • Wei-Hung Weng, Peter Szolovits
Information in electronic health records (EHR), such as clinical narratives, examination reports, lab measurements, demographics, and other patient encounter entries, can be transformed into appropriate data representations that can be used for downstream clinical machine learning tasks using representation learning.
1 code implementation • 19 Sep 2019 • Wei-Hung Weng
In this chapter, we provide a brief overview of applying machine learning techniques for clinical prediction tasks.
1 code implementation • 17 Sep 2019 • Wei-Hung Weng, Yuannan Cai, Angela Lin, Fraser Tan, Po-Hsuan Cameron Chen
Metadata are general characteristics of the data in a well-curated and condensed format, and have been proven to be useful for decision making, knowledge discovery, and also heterogeneous data organization of biobank.
no code implementations • 15 Aug 2019 • Szu-Yeu Hu, Wei-Hung Weng, Shao-Lun Lu, Yueh-Hung Cheng, Furen Xiao, Feng-Ming Hsu, Jen-Tang Lu
Stereotactic radiosurgery (SRS), which delivers high doses of irradiation in a single or few shots to small targets, has been a standard of care for brain metastases.
2 code implementations • WS 2019 • Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, Matthew B. A. McDermott
Contextual word embedding models such as ELMo (Peters et al., 2018) and BERT (Devlin et al., 2018) have dramatically improved performance for many natural language processing (NLP) tasks in recent months.
1 code implementation • 4 Apr 2019 • Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi
The automatic generation of radiology reports given medical radiographs has significant potential to operationally and improve clinical patient care.
1 code implementation • 4 Feb 2019 • Wei-Hung Weng, Yu-An Chung, Peter Szolovits
As patients' access to their doctors' clinical notes becomes common, translating professional, clinical jargon to layperson-understandable language is essential to improve patient-clinician communication.
no code implementations • 3 Dec 2018 • Uma M. Girkar, Ryo Uchimido, Li-wei H. Lehman, Peter Szolovits, Leo Celi, Wei-Hung Weng
Determining whether hypotensive patients in intensive care units (ICUs) should receive fluid bolus therapy (FBT) has been an extremely challenging task for intensive care physicians as the corresponding increase in blood pressure has been hard to predict.
no code implementations • 21 Nov 2018 • Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag, Matthew McDermott, Peter Szolovits
Joint embeddings between medical imaging modalities and associated radiology reports have the potential to offer significant benefits to the clinical community, ranging from cross-domain retrieval to conditional generation of reports to the broader goals of multimodal representation learning.
no code implementations • 4 Nov 2018 • Yu-An Chung, Wei-Hung Weng, Schrasing Tong, James Glass
We present a framework for building speech-to-text translation (ST) systems using only monolingual speech and text corpora, in other words, speech utterances from a source language and independent text from a target language.
no code implementations • 25 Jun 2018 • Wei-Hung Weng, Peter Szolovits
In this work, we utilized the embeddings alignment method for the word mapping between unparalleled clinical professional and consumer language embeddings.
no code implementations • NeurIPS 2018 • Yu-An Chung, Wei-Hung Weng, Schrasing Tong, James Glass
Recent research has shown that word embedding spaces learned from text corpora of different languages can be aligned without any parallel data supervision.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 2 Dec 2017 • Wei-Hung Weng, Mingwu Gao, Ze He, Susu Yan, Peter Szolovits
This work aims to learn personalized optimal glycemic trajectories for severely ill septic patients by learning data-driven policies to identify optimal targeted blood glucose levels as a reference for clinicians.
no code implementations • 22 Nov 2017 • Yu-An Chung, Wei-Hung Weng
Deep neural networks have been investigated in learning latent representations of medical images, yet most of the studies limit their approach in a single supervised convolutional neural network (CNN), which usually rely heavily on a large scale annotated dataset for training.