Performance metrics for BrC. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Proposed methodology. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Loss vs. Epoch. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Sample images from the BreakHis dataset. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Accuracy vs. Epoch. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

S1 Dataset - حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

CSCO’s flowchart. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Inconsistency concept for a triad (2, 5, 3). حسب Waldemar W. Koczkodaj (22008783)

"…The proposed regeneration method emulates three primary phases of a biological process: identifying the most damaged areas (by identifying inconsistencies in the pairwise comparison matrix), cell proliferation (filling in missing data), and stabilization (optimization of global consistency). …"

Data_Sheet_1_Machine Learning Prediction Model for Acute Renal Failure After Acute Aortic Syndrome Surgery.docx حسب Jinzhang Li (9221930)

Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx حسب Lian Li (49049)

"…Objective<p>This study utilizes real-world data from primary membranous nephropathy (PMN) patients to preliminarily develop a venous thromboembolism (VTE) risk prediction model with machine learning. …"

ResNeXt101 training and results. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Architecture of ConvNet. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Comparison of state-of-the-art method. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Proposed ResNeXt101 operational flow. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Proposed method approach. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

Descriptive statistics. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

Data_Sheet_1_Triage Modeling for Differential Diagnosis Between COVID-19 and Human Influenza A Pneumonia: Classification and Regression Tree Analysis.docx حسب Anling Xiao (11252973)

Data_Sheet_1_Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling.PDF حسب Nguyen Thanh Nhu (16400859)

Data_Sheet_1_Explainable ensemble machine learning model for prediction of 28-day mortality risk in patients with sepsis-associated acute kidney injury.doc حسب Jijun Yang (5119103)

Transect in parts of California. حسب Qinghua Li (398885)

"…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …"