Predictive_158_Data-18_input-1 and 5_output.csv by Esin Caglayan (21186749)

Data Sheet 1_Development of a novel artificial intelligence algorithm for interpreting fetal heart rate and uterine activity data in cardiotocography.docx by Rohit Pardasani (22253656)

“…</p>Methods<p>Fetal tracings sourced from 19 birthing centers through a US-based healthcare delivery organization were clinically interpreted, labeled, quality checked, and ratified by clinicians to be included in the study. The algorithm using deep learning and rule-based techniques was developed to identify segments of interest (accelerations, decelerations, and contractions). …”

Box plot of ablation experiment data. by Tengfei Ma (597633)

Data_Sheet_1_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.CSV by Jie Shen (31533)

Data_Sheet_2_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.docx by Jie Shen (31533)

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

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Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

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Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

Subjects:

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

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S1 Data - Machine learning-based prediction of metabolic dysfunction-associated steatotic liver disease using National Health and Nutrition Examination Survey (NHANES) data by Yong Zhang (5893)

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Mean(SD) AUC-ROC for Study Population and Demographic Subgroups by Classification Algorithm. by Elizabeth A. Campbell (3019293)

Supporting data for “Developing algorithms to optimize recommender system for self-regulated learning promotion in online contexts: a design-based study” by Long Zhang (11129139)

Confusion Matrix for the Hybrid algorithms. by Faten Al-hussein (20707521)

“…Medical records from 3,000 King Abdulaziz University Hospital patients containing demographic, lifestyle, and lipid profile data were used to develop the models. For the first time, we utilized recommended machine learning algorithms to develop hybrid prediction models to reduce the number of significant KPIs while enhancing HbA1c prediction accuracy. …”

Explained variance of features subsets using different machine learning algorithms: Fig 3 shows all the possible combinations of feature subsets, according to S3 Table in S1 Data, with corresponding explained variance estimated using different machine learning algorithms (Lasso, Ridge Regression, Support Vector Regression (SVR) and Extra Trees). by Qasim Bukhari (20896572)

Scatter plots of actual and forecasted values of different optimization algorithms for BiLSTM models in corn and wheat datasets. by Kaixuan Sun (4739976)

General architecture of XGBoost algorithm. by Saghir Ahmed (4416544)

Predictions of weekly newly reported cases of BC for the upcoming 16 weeks since 7 January 2024 using a two-VOCs model learned by the VOCs-INN algorithm. by Wenxuan Li (2566450)

Summary of the metrics of the different trained models foreach algorithm in each split for each dataset. by Jaime B. Matas-Bustos (21772430)

Summary of the metrics of the different trained algorithms that performed best in the Testing process for each dataset. by Jaime B. Matas-Bustos (21772430)