Analysis of CM1 ROC curve. by Mohd Mustaqeem (19106494)

“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”

SPAM-XAI confusion matrix using PC1 dataset. by Mohd Mustaqeem (19106494)

“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”

Analysis PC1 AU-ROC curve. by Mohd Mustaqeem (19106494)

“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”

Data_Sheet_1_Early detection of sepsis using machine learning algorithms: a systematic review and network meta-analysis.pdf by Mikhail Ya Yadgarov (18543769)

Table_1_Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer.docx by Yalong Zhang (711724)

Image_2_Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer.TIF by Yalong Zhang (711724)

Image_3_Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer.TIF by Yalong Zhang (711724)

Image_1_Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer.TIF by Yalong Zhang (711724)

A Comprehensive Review on Evolution Behavior of Particle Size Distribution During Fine Grinding Process for Optimized Separation Purposes by Wang Guo (229598)

“…This comprehensive review delves into six crucial facets, offering a systematic appraisal: (1) the statistical framework and evaluation methodologies for characterizing particle size distribution, which includes the intricacy of model analysis and interpretation; (2) the property of grinding products, which emphasizes the physicochemical attribute that influences the sorting efficiency and the product quality; (3) grinding kinetics models, which emphasizes the integration of advanced algorithms and experimental validations; (4) the intricate relationship between characteristic particle size and energy consumption, which elucidates the mechanistic underpinning of particle size reduction and energy consumption; (5) stress intensity theory, which elucidates the role of mechanical forces in particle breakage and size reduction; and (6) optimization techniques tailored toward achieving the desired particle size interval, which highlights the grinding technical efficiency and the attainable region method inherent in optimizing the operation parameter of mills. …”

Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra (17387852)

“…The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”

Table1_Warfarin anticoagulation management during the COVID-19 pandemic: The role of internet clinic and machine learning.DOCX by Meng-Fei Dai (12324617)

“…This study aimed to optimize warfarin treatment during the COVID-19 pandemic by determining the role of the Internet clinic and developing a machine learning (ML) model to predict anticoagulation quality.…”

Extraction and expression of architectural color. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

Basic color value distribution map of the street. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

SegNet architecture. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

Overview of workflow. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

Descriptive statistics for the volunteers. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

Jiefang North Road Street. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

Colors with different number of clusters. by Xin Han (1329648)

“…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …”

Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP by Xiaofeng Wang (119575)

Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx by Yuan Liu (88411)

“…Afterward, we utilized a two-stage feature space optimization strategy to improve the feature representation ability, and trained a predictive model using support vector machine (SVM). …”