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2024 IEEE-EMBS International Conference on Biomedical and health Informatics, BHI 2024

作者： Healey, Elizabeth Kohane, Isaac Harvard-MIT Program in Health Sciences and Technology CambridgeMA United States

ISBN: (纸本)9798350351552

In recent years, the number of patients using continuous glucose monitoring (CGM) has increased. In addition to helping patients manage their disease, CGM produces time series data that can be used for integration in control algorithms, predictive models, and for retrospective analyses. Through feature extraction, many digital biomarkers can be derived from CGM. In this work, we provide a tool to extract features derived from the frequency domain. We first introduce a novel open-source Python library, CGM-Freq, for the analysis of CGM data in the frequency domain. We then test the library on real data. This work provides an open-source tool to further investigate the frequency domain of CGM signals. © 2024 IEEE.

关键词： Disease control

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Model-Based Insulin Sensitivity and Beta-Cell Function Estimation from Daily Continuous Glucose Monitoring 46

Model-Based Insulin Sensitivity and Beta-Cell Function Estim...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Healey, Elizabeth Kohane, Isaac Harvard-MIT Program in Health Sciences and Technology CambridgeMA United States Harvard Medical School Department of Biomedical Informatics BostonMA United States

ISBN: (纸本)9798350371499

Type 2 diabetes (T2D) is a prevalent chronic illness with many different options for treatment management. Continuous glucose monitors (CGM) offer physiological data that clinicians can access when making treatment decisions. However, the utility of CGM in management of T2D remains an active area of research. In our work, we demonstrate the feasibility of exploiting raw daily CGM data to estimate the physiological parameters of insulin sensitivity and beta-cell function that correlate with estimates derived from laboratory findings. We use a peak extraction algorithm to extract peaks from daily CGM data and implement a model-based approach to infer physiological parameters. We demonstrate that the inferred parameter estimates of insulin sensitivity and beta-cell function correlate to the ground truth measurements as determined by an oral glucose tolerance test (OGTT). © 2024 IEEE.

关键词： Physiological models

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Role of Prefrontal Cortex Circuitry in Maintaining Social Homeostasis

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Biological Psychiatry 2025年第10期97卷 953-960页

作者： Lee, SeungHyun Williams, Ziv M. Department of Neurosurgery Massachusetts General Hospital Harvard Medical School Boston Massachusetts United States Harvard-MIT Division of Health Sciences and Technology Boston Massachusetts United States Program in Neuroscience Harvard Medical School Boston Massachusetts United States

Homeostasis is a fundamental concept in biology and ensures the stability of life by maintaining the constancy of physiological processes. Recent years have witnessed a surge in research interest in these physiological processes, with a growing focus on understanding the mechanisms underlying social homeostasis. This shift in focus underscores our increasing understanding of the importance of social interactions and their impact on individual well-being. In this review, we explore the interconnected research across 3 primary categories: understanding the neural mechanisms influencing set points, defining contemporary factors that can disrupt social homeostasis, and identifying the potential contributions of social homeostatic failure in the development of psychiatric diseases. We also delve into the role of the prefrontal cortex and its circuitry in regulating social behavior, decision-making processes, and the manifestation of neuropsychiatric disorders, such as depression and anxiety. Finally, we examine the influence of more recent factors such as growing social media exposure and the COVID-19 pandemic on mental health, highlighting their disruptive effects. We also identify gaps in current literature through the analysis of research trends and propose future research directions to advance our understanding of social homeostasis, with implications for mental health interventions. © 2024 Society of Biological Psychiatry

关键词： COVID Homeostasis Media Neuroscience Prefrontal Social

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CGM-Freq: A Python Library for Frequency Domain Analysis of Continuous Glucose Monitoring Data

CGM-Freq: A Python Library for Frequency Domain Analysis of ...

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IEEE EMBS International Conference on Information technology Applications in Biomedicine (ITAB)

作者： Elizabeth Healey Isaac Kohane Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA

ISBN: (数字)9798350351552

ISBN: (纸本)9798350351569

关键词： Continuous glucose monitoring Frequency-domain analysis Time series analysis Signal processing algorithms Signal processing Predictive models Feature extraction Prediction algorithms Libraries Diseases

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The Future of Drug Delivery

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CHEMISTRY OF MATERIALS 2023年第2期35卷 359-363页

作者： Gao, Jingjing Karp, Jeffrey Langer, Robert Joshi, Nitin Center for Nanomedicine Department of Anesthesiology Perioperative and Pain Medicine Brigham and Women’s Hospital Boston Massachusetts 02115 United States Harvard Medical School Boston Massachusetts 02115 United States Harvard-MIT Program in Health Sciences and Technology MIT Cambridge Massachusetts 02139 United States Harvard Stem Cell Institute Cambridge Massachusetts 02138 United States Broad Institute of MIT and Harvard Cambridge Massachusetts 02142 United States Department of Chemical Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02142 United States Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge Massachusetts 02142 United States

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Model-Based Insulin Sensitivity and Beta-Cell Function Estimation from Daily Continuous Glucose Monitoring

Model-Based Insulin Sensitivity and Beta-Cell Function Estim...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Elizabeth Healey Isaac Kohane Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

关键词： Sensitivity Biological system modeling Estimation Data models Diabetes Data mining Insulin Engineering in medicine and biology

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Probabilistic genotype-phenotype maps reveal mutational robustness of RNA folding, spin glasses, and quantum circuits

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Physical Review Research 2025年第1期7卷 013118-013118页

作者： Anna Sappington Vaibhav Mohanty Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard-MIT Program in Health Sciences and Technology Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard/MIT MD-PhD Program Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Chemistry and Chemical Biology Harvard University Cambridge Massachusetts 02138 USA

Recent studies of genotype-phenotype maps have reported universally enhanced phenotypic robustness to genotype mutations, a feature essential to evolution. Virtually all of these studies make a simplifying assumption that each genotype—represented as a sequence—maps deterministically to a single phenotype, such as a discrete structure. Here we introduce probabilistic genotype-phenotype (PrGP) maps, where each genotype maps to a vector of phenotype probabilities, as a more realistic and universal language for investigating robustness in a variety of physical, biological, and computational systems. We study three model systems to show that PrGP maps offer a generalized framework which can handle uncertainty emerging from various physical sources: (1) thermal fluctuation in RNA folding, (2) external field disorder in the spin-glass ground state search problem, and (3) superposition and entanglement in quantum circuits, which are realized experimentally on IBM quantum computers. In all three cases, we observe a biphasic robustness scaling which is enhanced relative to random expectation for more frequent phenotypes and approaches random expectation for less frequent phenotypes. We derive an analytical theory for the behavior of PrGP robustness, and we demonstrate that the theory is highly predictive of empirical robustness.

关键词： Quantum computers

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Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series

arXiv

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arXiv 2023年

作者： Raghu, Aniruddh Chandak, Payal Alam, Ridwan Guttag, John Stultz, Collin M. Massachusetts Institute of Technology CambridgeMA United States Harvard-MIT Program in Health Sciences and Technology CambridgeMA United States

Self-supervised learning (SSL) for clinical time series data has received significant attention in recent literature, since these data are highly rich and provide important information about a patient’s physiological state. However, most existing SSL methods for clinical time series are limited in that they are designed for unimodal time series, such as a sequence of structured features (e.g., lab values and vitals signs) or an individual high-dimensional physiological signal (e.g., an electrocardiogram). These existing methods cannot be readily extended to model time series that exhibit multimodality, with structured features and high-dimensional data being recorded at each timestep in the sequence. In this work, we address this gap and propose a new SSL method — Sequential Multi-Dimensional SSL — where a SSL loss is applied both at the level of the entire sequence and at the level of the individual high-dimensional data points in the sequence in order to better capture information at both scales. Our strategy is agnostic to the specific form of loss function used at each level – it can be contrastive, as in SimCLR, or non-contrastive, as in VICReg. We evaluate our method on two real-world clinical datasets, where the time series contains sequences of (1) high-frequency electrocardiograms and (2) structured data from lab values and vitals signs. Our experimental results indicate that pre-training with our method and then fine-tuning on downstream tasks improves performance over baselines on both datasets, and in several settings, can lead to improvements across different self-supervised loss functions. Copyright © 2023, The Authors. All rights reserved.

关键词： Supervised learning

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Hering's opponent-colors theory fails a key test in a non-Western culture 44

Hering's opponent-colors theory fails a key test in a non-We...

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44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022

作者： Conway, Bevil R. Malik-Moraleda, Saima Gibson, Edward Laboratory of Sensorimotor Research National Eye Institute National Institute of Mental Health Program in Speech and Hearing Bioscience and Technology Harvard University United States Department of Brain and Cognitive Sciences MIT

Opponent Colors Theory advances that four colors have special status and are yoked in opponent fashion (yellow-versus-blue, and red-versus-green). Classic hue cancelation studies provide evidence for this theory: people readily pick out colors that are neither red nor green, usually yellow. Here we conducted a version of a hue-cancelation experiment with the Tsimane' people, a nonindustrialized culture in the Amazon. Tsimane' speakers readily identified reddish and greenish color chips, but they showed idiosyncratic choices when asked to identify a color that is neither reddish nor greenish, unlike English speakers who consistently select focal yellow. The Tsimane' participants who also spoke Spanish and had a consistent label for English "yellow" ("amarillo"), performed similarly to the Tsimane' monolinguals, suggesting that simply having a label for "yellow" is not sufficient to explain the consistency of English speakers. The results add to a growing body of evidence that does not support Opponent Colors Theory. © 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY)

关键词： Color

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Functional Neuroimaging via Diffuse Correlation Spectroscopy at 1064nm

Functional Neuroimaging via Diffuse Correlation Spectroscopy...

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Optics and the Brain, BRAIN 2022

作者： Ozana, Nisan Lue, Niyom Renna, Marco Robinson, mitchell Martin, Alyssa Blackwell, Megan Carp, Stefan A. Franceschini, Maria A. Massachusetts General Hospital and Harvard Medical School Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology BostonMA United States MIT Lincoln Laboratory LexingtonMA United States MIT Health Sciences and Technology Program CambridgeMA United States

In this paper, we present a continuous wave (CW) and time-domain (TD) diffuse correlation spectroscopy (DCS) for cerebral blood flow monitoring at 1064nm. Findings show high brain sensitivity and fast monitoring which... 详细信息

ISBN: (纸本)9781957171036

关键词： Neuroimaging

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