Paired t-test for detecting the difference between DMFDEM errors and other types of DEM errors. by Qinghua Li (398885)

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…In general, BRBPNN does not show any optimization adaption methods to determine the optimal parameter for appropriate detection. Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

UMAFall: Fall Detection Dataset (Universidad de Malaga) by Eduardo Casilari (3333906)

“…The traces are aimed at evaluating fall detection algorithms.<div>Several video clips describing the performed movements are also included.…”

Data processing flow diagram. by Carl D. Snyder (20868650)

G4SNVHunter workflow for identifying variants that affect G4 formation. by Rongxin Zhang (1618159)

Conserved motif analysis of Human and <i>Leishmania Strumpellin</i> proteins using MEME suite. by Yusr Saadi-Ben Aoun (20469385)

A schematic representation of pairwise whole genome comparisons in all possible pairwise combinations (n by Klára Janečková (8655201)

Table 1_Optimization of diagnosis-related groups for patients with acute appendicitis using a machine learning model.docx by Xinlong Gu (22163251)

“…Additionally, a classification and regression tree (CART) model, based on the exhaustive chi-square automatic interaction detection (E-CHAID) algorithm, was applied to establish the DRG grouping model.…”

Data Sheet 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.pdf by Dibash Basukala (20772110)

“…Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. …”

Image 2_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

“…Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. …”

Image 4_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

“…Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. …”

Image 3_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

“…Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. …”

Image 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

“…Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. …”

Image 5_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg by Dibash Basukala (20772110)

“…Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. …”

SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM) by Xiang Cheng (20496924)

“…The SynthSoM dataset is open-sourced and provides consistent data for cross-comparing SoM-related algorithms.…”

Data Sheet 1_Deeper eelgrass meadows are refugia from disease and environmental stressors.docx by Olivia J. Graham (11671054)

“…Leveraging a machine-learning algorithm to detect and quantify disease, we measured high disease levels and large changes in meadow densities, particularly in the warmer 2018 summer. …”

Data Sheet 1_Artificial intelligence in hospital infection prevention: an integrative review.docx by Rabie Adel El Arab (14113425)

“…Comparative data suggest that while both machine learning and deep learning approaches perform well, some deep learning models may offer slight advantages in complex data environments. Advanced algorithms, including neural networks, decision trees, and random forests, significantly improved detection rates when integrated with EHRs, enabling real-time surveillance and timely interventions. …”