Integrating urinary metabolomics and clinical datasets for multi-cancer detection by Dongyong Lee (18786694)

“…SERS intensity (arbitrary units)</p><p dir="ltr">- All spectra have a uniform number of data points (rows) per file.</p><p dir="ltr">- No baseline correction, smoothing, normalization, or other signal processing has been applied. …”

The 2009 FDA PRO guidance, Potential Type I error, Descriptive Statistics and Pragmatic estimation of the number of interviews for item elicitation by Josh Fleckner (22075124)

“…The URN model provides a framework to demonstrate that an algorithm such as “first interview with zero new codes” may establish that all codes have been elicited. …”

How voice biomarkers have been used in heart failure management: a scoping review by Yufan Yang (8250309)

“…Most studies (12/19) developed new algorithms for data analysis. Model performance was mainly evaluated by accuracy (10/19), sensitivity (7/19), and specificity (6/19). …”

TreeMap 2016: A tree-level model of the forests of the conterminous United States circa 2016 by Karin L. Riley (19657882)

“…We used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). …”

<b>Measurement </b><b>m</b><b>ethod for </b><b>b</b><b>ogie </b><b>s</b><b>teel </b><b>s</b><b>pring </b><b>p</b><b>arameters </b><b>b</b><b>ased on 3D </b><b>s</b><b>tructured </b... by xinpeng shi (16710936)

“…The end-face point cloud then undergoes iterative plane fitting, and the spring height is determined by combining this with a projection-based height measurement algorithm. Finally, a boundary extraction method is introduced to process the end-face point cloud data, where the spring radius is obtained through a circle-fitting algorithm. …”

Supplementary information files for "Explainable machine learning models for predicting the ultimate bending capacity of slotted perforated cold-formed steel beams under distortion... by L Simwanda (19921680)

“…Utilizing a dataset from 432 non-linear finite element analysis simulations of CFS Lipped channels, ten ML algorithms, including four basic and six ensemble models, were evaluated. …”

Table 2_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Future efforts should aim to enhance the standardization of data processing, feature selection, and validation processes. …”

Table 4_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Future efforts should aim to enhance the standardization of data processing, feature selection, and validation processes. …”

Table 3_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Future efforts should aim to enhance the standardization of data processing, feature selection, and validation processes. …”

Table 1_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Future efforts should aim to enhance the standardization of data processing, feature selection, and validation processes. …”

Portable Library for Reinforcement Learning on Cloud Cyberinfrastructure by Sanmukh Kuppannagari (21798863)

“…Moreover, existing research on reducing the execution time of RL is inaccessible to RL application developers as they require expertise in designing careful compute orchestration among different types of hardware devices (such as Graphics Processing Units (GPU), Field Programmable Gate Arrays (FPGA)) available in modern data centers. …”

Development of Compute-Intensive Web Applications with Native Desktop Performance by Zahir Toufie (18869185)

“…</p><h2><u>Set 1</u></h2><p dir="ltr"><b>System23 versus Native benchmarking</b> data based on Polybench/C algorithms. The testing environment within which the benchmarks were executed comprised of a standard Intel-based computer system containing an Intel i7-7567U CPU with a clock speed of 3.50GHz. …”

Supplementary file 1_RadioMe: an automated home-based radio, music playlist, and diary reminder system: Report on recruitment, music compilation, and listening, and preliminary tes... by Alexander Street (16905678)

“…</p>Materials and methods<p>In stage 1, a playlist compilation process was co-designed with a lived experience group; HR and behavioural data were collected by participants when agitated to refine the algorithm used for automated music activation; 15 home visits were conducted to compile and test the playlists, collecting video, HR, and autobiographical data in each session to inform on playlist suitability for NPS management. …”

Gaze Inputs for Targeting: The Eyes Have It, Not With a Cursor by Ajoy S. Fernandes (22293773)

“…If the participant looked out of the grid boundary, on button press, we chose to select the last targeted element, but no other algorithms to enhance performance were employed. …”

Revised supplementary material by Shijie Qin (11057652)

TreeMap 2020 CONUS: A tree-level model of the forests of the conterminous United States circa 2020 by Scott N. Zimmer (20807459)

“…We used a Random Forest machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE) and Daymet (Daymet). …”

TreeMap 2022 CONUS: A tree-level model of the forests of the conterminous United States circa 2022 by Rachel M. Houtman (19658365)

“…We used a Random Forest machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE) and Daymet (Daymet). …”

A Dataset on the Biodiversity Footprints and Sectoral Differences in China by haiyue wang (20803663)

“…It comprises the following components: (1) China’s raw species spatial data, sourced from the IUCN and BirdLife International, with 446 threatened and near-threatened species attributes provided in a CSV file. (2) Biodiversity footprint data of China's 19 economic sectors across 30 provinces (2017), with two versions: Version 1: 352 species (excluding NT species) Version 2: 446 species (including NT species) Stored as “2017 China Provincial Biodiversity Footprint Data” in Shapefile format. (3) Biodiversity footprint data by taxonomic group (Mammal, Amphibian, Reptile, and Bird) across 30 provinces (2017), with two versions as above, stored as “2017 China Taxonomic Biodiversity Footprint Data” in Shapefile format. (4) A procedural demonstration of matrix operations with detailed algorithmic steps for specific species, stored as “An example detailing the computational steps for specific species” in PDF format. (5) Code.…”

Table 1_An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments.docx by Zhenling Dai (22011134)

“…In this study, we aim to explore the role of the cGAS-STING pathway in breast cancer immunotherapy resistance.</p>Methods<p>Multiple machine learning algorithms were applied to construct an immunotherapy subgroup model and in vitro experiments were performed to verify the HOXC13 in regulating BRCA immunity.…”

Image 2_An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments.tif by Zhenling Dai (22011134)

“…In this study, we aim to explore the role of the cGAS-STING pathway in breast cancer immunotherapy resistance.</p>Methods<p>Multiple machine learning algorithms were applied to construct an immunotherapy subgroup model and in vitro experiments were performed to verify the HOXC13 in regulating BRCA immunity.…”