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cog-bias-med-llms's Introduction

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About me

First year Ph.D. student at Johns Hopkins University, Department of Biomedical Engineering. Advised by Rama Chellappa (primary) and Suchi Saria. Working on projects related to multimodal modeling of irregularly sampled clinical time series data, pre-surgical risk stratification with ECG (with Robert Stevens), and conformal prediction of healthcare outcomes (with Prasanna Santhanam).

Previously

I spent two years as a postbaccalaureate IRTA at the National Institutes of Mental Health, in the Data Science and Sharing Team and Machine Learning Team. I worked applied projects realted to machine learning to healthcare and neuroscience. In particular:

  • [Applied ML]: Machine learning models for predicting longitudinal mental health outcomes during the COVID-19 pandemic
  • [Stat. methods]: Detecting context-dependent changes in neural encoding from longitudinal electrophysiological recordings
  • [Applied ML]: 3D pose estimation & unsupervised behavior classification of animals in video
  • [Open science]: Improving standardization of two-photon and holographic photostimulation archival data formats

Education

I graduated magna cum laude from Dartmouth College in June 2021, with a double major in applied mathematics and neuroscience (high honors) and a minor in economics. I worked on research related to adaptive learning and decision making under uncertainty in Alireza Soltani's lab, and on projects related to animal tracking and behavior classification in Peter Tse's octpus lab. I was also on the men's Varsity Lightweight Rowing team.

cog-bias-med-llms's People

Contributors

carlwharris avatar imessien avatar samuelschmidgall avatar tawsifur avatar

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cog-bias-med-llms's Issues

Some Question in FuseMoE

HI,

I'm very sorry for asking FuseMoE related questions in this repository, as there is no place to submit issues in FuseMoE.

When preprocessing the mimic-iv, we didn't find the generation code for ts_labs_vitals_icu.pkl, but there is a code for output ts_labs_vitals.pkl, are they the same?

If not same could you please provide the generation code. And It would be great if the google drive mentioned here could be provided!

Also, when we tried to embedd the ecg, 'attia_encoder_256.keras' was not found. We observe that you mentioned in your paper: ' We adopt a convolutional autoencoder approach, adapted from Attia et al. (2019), that compresses each ECG into a 256-dimensional
vector.'
Would it be possible to provide the training code, and it would be nice if it was already trained attia_encoder_256.keras.

status_quo

This one doesnt really make any sense

@imessien @tawsifur @Danolsh @carlwharris not sure who did this one

 elif bias_type=="status_quo":
        opts= [_ for _ in options.split(r'", "')]
        opts[0] = opts[0][1:]
        opt_letters = [op[:1] for op in opts]
        opt_letters.remove(answer_option)
        adv_option = np.random.choice(opt_letters)
        num = {"A": 0, "B": 1, "C": 2, "D": 3, "E": 4}[adv_option]
        prompt += f" Your hospital has been using \"{opts[num]}\" for the past 10 years."

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