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. …"

Segmentation results of the proposed model. 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. …"

Dendrogram of the stock prices. حسب Muhammad Hilal Alkhudaydi (21560690)

"…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …"

Descriptive statistics on stock prices. حسب Muhammad Hilal Alkhudaydi (21560690)

"…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …"

Correlation heatmap of the principal components. حسب Muhammad Hilal Alkhudaydi (21560690)

"…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …"

Data_Sheet_2_Computational Neural Modeling of Auditory Cortical Receptive Fields.pdf حسب Jordan D. Chambers (6732224)

Data_Sheet_1_Computational Neural Modeling of Auditory Cortical Receptive Fields.PDF حسب Jordan D. Chambers (6732224)

Data_Sheet_3_Computational Neural Modeling of Auditory Cortical Receptive Fields.PDF حسب Jordan D. Chambers (6732224)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. حسب Martijn A. de Jong (17896732)

Proposed reinforcement learning architecture. حسب Enoch Solomon (21416703)

"…<div><p>In the realm of game playing, deep reinforcement learning predominantly relies on visual input to map states to actions. The visual data extracted from the game environment serves as the primary foundation for state representation in reinforcement learning agents. …"

Schematic representation of semi-automated algorithm for organoids analyzing. حسب Anna Demchenko (18449439)

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_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx حسب Çaǧlar Çaǧlayan (12253934)

"…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …"

S2 Data - حسب Musab A. Isak (18824223)

S1 Data - حسب Musab A. Isak (18824223)

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics حسب Zhichao Liu (191718)

"…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …"