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

“…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …”

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

“…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …”

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

“…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …”

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

“…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …”

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

“…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …”

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

“…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …”

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

“…The SynthSoM dataset encompasses multiple data modalities, including radio-frequency (RF) channel large-scale and small-scale fading data, RF millimeter wave (mmWave) radar sensory data, and non-RF sensory data, e.g., RGB images, depth maps, and light detection and ranging (LiDAR) point clouds. …”

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

“…</p>Results<p>AI models demonstrated high predictive accuracy for the detection, surveillance, and prevention of multiple HAIs, with models for surgical site infections and urinary tract infections frequently achieving area-under-the-curve (AUC) scores exceeding 0.80, indicating strong reliability. …”