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pro vyhledávání: '"Engstrom P"'
With the digitization of health data, the growth of electronic health and medical records lowers barriers for using algorithmic techniques for data analysis. While classical machine learning techniques for health data approach commercialization, ther
Externí odkaz:
http://arxiv.org/abs/2410.02446
Autor:
Sonar, Vivek Ganesh, Jan, Muhammad Tanveer, Wells, Mike, Pandya, Abhijit, Engstrom, Gabriela, Shih, Richard, Furht, Borko
Accurate body weight estimation is critical in emergency medicine for proper dosing of weight-based medications, yet direct measurement is often impractical in urgent situations. This paper presents a non-invasive method for estimating body weight by
Externí odkaz:
http://arxiv.org/abs/2410.02800
Autor:
Letchev, Stanimir, Crepp, Justin R., Abbott, Caleb G., Hersey, Ryan, Engstrom, Matthew, Baggett, Nicholas
Local amplitude aberrations caused by scintillation can impact the reconstruction process of a wavefront sensor (WFS) by inducing a spatially non-uniform intensity at the pupil plane. This effect is especially relevant for the commonly-used Shack-Har
Externí odkaz:
http://arxiv.org/abs/2407.14606
We present algorithms that substantially accelerate partition-based cross-validation for machine learning models that require matrix products $\mathbf{X}^\mathbf{T}\mathbf{X}$ and $\mathbf{X}^\mathbf{T}\mathbf{Y}$. Our algorithms have applications in
Externí odkaz:
http://arxiv.org/abs/2401.13185
When selecting data for training large-scale models, standard practice is to filter for examples that match human notions of data quality. Such filtering yields qualitatively clean datapoints that intuitively should improve model behavior. However, i
Externí odkaz:
http://arxiv.org/abs/2401.12926
There is an increasing need to comprehensively characterize the kinematic performances of different Micromobility Vehicles (MMVs). This study aims to: 1) characterize the kinematic behaviors of different MMVs during emergency maneuvers; 2) explore th
Externí odkaz:
http://arxiv.org/abs/2312.14717
Autor:
Engstrøm, Ole-Christian Galbo, Dreier, Erik Schou, Jespersen, Birthe Møller, Pedersen, Kim Steenstrup
Based on previous work, we assess the use of NIR-HSI images for calibrating models on two datasets, focusing on protein content regression and grain variety classification. Limited reference data for protein content is expanded by subsampling and ass
Externí odkaz:
http://arxiv.org/abs/2311.04042
Autor:
Mahnaz Samadbeik, Teyl Engstrom, Elton H Lobo, Karem Kostner, Jodie A Austin, Jason D Pole, Clair Sullivan
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Background Lipid disorders significantly increase cardiovascular disease (CVD) risk, the leading cause of mortality worldwide. Effective lipid management is critical for improving health outcomes. Traditional screening methods face challenge
Externí odkaz:
https://doaj.org/article/a6fd3dcee3ec48c1940670f02bc5ccea
Autor:
Si Lok, Timothy N. H. Lau, Brett Trost, Amy H. Y. Tong, Tara Paton, Richard F. Wintle, Mark D. Engstrom, Anne Gunn, Stephen W. Scherer
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract The muskox (Ovibos moschatus), an integral component and iconic symbol of arctic biocultural diversity, is under threat by rapid environmental disruptions from climate change. We report a chromosomal-level haploid genome assembly of a muskox
Externí odkaz:
https://doaj.org/article/7c530920e7624924a0cb307d81999c43
Autor:
Leclerc, Guillaume, Ilyas, Andrew, Engstrom, Logan, Park, Sung Min, Salman, Hadi, Madry, Aleksander
We present FFCV, a library for easy and fast machine learning model training. FFCV speeds up model training by eliminating (often subtle) data bottlenecks from the training process. In particular, we combine techniques such as an efficient file stora
Externí odkaz:
http://arxiv.org/abs/2306.12517