Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm حسب Hussein Ali Bardan (21976208)

"…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …"

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf حسب Jan Tönshoff (10192709)

Reconstruction results of a central slice of MPRAGE data at 3T. حسب Chi Zhang (9857)

Reconstruction results of a central slice of MPRAGE data at 7T. حسب Chi Zhang (9857)

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf حسب Muhammad Awais (263096)

"…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"

Table 3_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx حسب Jian Wang (5901)

"…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …"

Table 1_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx حسب Jian Wang (5901)

"…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …"

Image 1_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.tif حسب Jian Wang (5901)

"…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …"

Table 2_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx حسب Jian Wang (5901)

"…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …"