Statistics of GI data processing using different algorithms at various input CTTDs. by Ki Hyun Nam (5813819)

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Graphical representation of the dial data and its classification into epochs using our algorithm. by Eleftheria Pistolas (20313429)

Statistics of HEWL data processing using different algorithms at various input CTTDs. by Ki Hyun Nam (5813819)

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The details of the results related to the evaluated algorithms. by Mohammadreza Namdar (22439057)

Algorithm assessment of temporal drought class using TPM. by Muhammad Asif Khan (7367468)

Consistency results of raw data. by Haotong Han (20855036)

“…</p><p>Methods</p><p>An information security analysis model based on the combination of KMC and DT algorithms is established. …”

Table 1_Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms.docx by Zhao Chen (92571)

“…We constructed a SEML model for MDD detection, incorporating three conventional machine learning algorithms as base models and a Neural Network (NN) as the meta-model. …”

Algorithms, data type, and accuracy. by Humaira Anzum (21416682)

“…Many researches have been undertaken to use computer vision on MRI images, and their accuracy ranges from 80–90%, new computer vision algorithms and cutting-edge transformers have the potential to improve this performance.We utilize advanced transformers and computer vision algorithms to enhance diagnostic accuracy, achieving an impressive 99% accuracy in categorizing Alzheimer’s disease stages through translating RNA text data and brain MRI images in near-real-time. …”

QuanFormer: A Transformer-Based Precise Peak Detection and Quantification Tool in LC-MS-Based Metabolomics by Zhengyi Zhang (518028)

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QuanFormer: A Transformer-Based Precise Peak Detection and Quantification Tool in LC-MS-Based Metabolomics by Zhengyi Zhang (518028)

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Baseline data table. by Jie Chu (293795)

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Data and code used in this article. by Yazhen Zhu (3595430)

Mortality of MM patients based on the MYLORD algorithm (2014–2020). by Cyrille Touzeau (14982494)

Table 1_Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a retrospective analysis based on MIMIC-IV database.docx by Wei Zhu (23646)

Image 5_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.jpeg by Xu Chen (432759)

“…LASSO regression was used for feature selection, and the predictive performance of logistic regression was compared with six machine learning algorithms. …”

Image 1_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…LASSO regression was used for feature selection, and the predictive performance of logistic regression was compared with six machine learning algorithms. …”

Image 2_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…LASSO regression was used for feature selection, and the predictive performance of logistic regression was compared with six machine learning algorithms. …”

Image 4_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…LASSO regression was used for feature selection, and the predictive performance of logistic regression was compared with six machine learning algorithms. …”

Image 3_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.tif by Xu Chen (432759)

“…LASSO regression was used for feature selection, and the predictive performance of logistic regression was compared with six machine learning algorithms. …”

Table 1_A machine learning model based on emergency clinical data predicting 3-day in-hospital mortality for stroke and trauma patients.docx by Xu Chen (432759)

“…LASSO regression was used for feature selection, and the predictive performance of logistic regression was compared with six machine learning algorithms. …”