Data Sheet 1_Flow-based parameterization for DAG and feature discovery in scientific multimodal data.pdf by Elise Walker (19937997)

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms by Guangyin Jia (21075537)

“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”

The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

Figure 1 from DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways by Zhaoxiang Cai (20445441)

Screening of palmitoylation genes based on machine learning algorithms. by Qijun Wo (12992781)

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Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif by Xuehui Fan (10762662)

Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

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Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

Comparison of federated learning algorithms. by Duy-Dong Le (22057362)

Data Sheet 1_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.pdf by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Algorithm flow based on CL-EPIDTN. by Fang Yang (123514)

3D CNN encoder. by Xueliang Guo (4797057)

“…To overcome these challenges, we introduce an advanced neuroimaging technology based on deep learning, the SWI-BITR-UNet model. …”

Table 2_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.xlsx by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Table 4_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.xlsx by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Table 3_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.xlsx by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Table 1_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.xlsx by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Table 5_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.xlsx by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Table 6_A novel lossless encoding algorithm for data compression–genomics data as an exemplar.xlsx by Anas Al-okaily (20601458)

“…In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. …”

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.</p><p>Materials and methods</p><p>This study used the latest nationally representative cross-sectional Bangladesh demographic health survey (BDHS), 2017–18 data. …”

ROC comparison of machine learning algorithm. by Balraj Preet Kaur (20370832)

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