Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…Potentially disregarded age-related ECG variations may result from skewed age data in training sets. ECG patterns are affected by physiological differences between the sexes; a dataset that is inclined toward one sex may compromise the accuracy of the others. …”

Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review by Daksh Dave (17949239)

“…This review focuses on the diagnostic accuracy of AI-assisted mammography, synthesizing findings from studies across different clinical settings and algorithms. The motivation for this research lies in addressing the need for enhanced diagnostic tools in breast cancer screening, where early detection can significantly impact patient outcomes. …”

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Here, the Quantized Identical Data Imputation (QIDI) mechanism is implemented at first for data preprocessing and normalization. …”

Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…Future research should focus on refining algorithms, ensuring real‐time adaptability, addressing ethical considerations, evaluating long‐term patient outcomes, fostering cooperative systems, and integrating relevant data and policies within the healthcare framework.…”

Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
Get full text
Get full text
Get full text
Get full text

Cross entropy error function in neural networks by Nasr, G.E.

“…To forecast gasoline consumption (GC), the ANN uses previous GC data and its determinants in a training data set. …”
Get full text
Get full text
Get full text

Video features with impact on user quality of experience by Abbas, Nadine

“…We conduct experimental measurements and record videos with different frame rate, video resolution, transmission data rate, packet loss, delay and codec types. After collecting the QoE assessments, the supervised training data set is developed and imported into Rapid-Miner data mining tool. …”
Get full text
Get full text
Get full text
Get full text

A new approach and faster exact methods for the maximum common subgraph problem by Abu-Khzam, Faisal N.

“…A detailed analysis shows that the proposed algorithm requires O((m+1)n) time, which is a superior worst-case bound to those known for previously-analyzed algorithms in the setting of the MCS problem. …”
Get full text
Get full text
Get full text
Get full text

Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…Wearable devices (WDs) make use of sensors historically reserved for hospital settings. WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”

Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles by Wadi, Ali

“…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
Get full text

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition.…”

Digital Image Watermarking Using Balanced Multiwavelets by Ghouti, L.

“…In this paper, a robust watermarking algorithm using balanced multiwavelet transform is proposed. …”
Get full text

Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier by Yassine Himeur (14158821)

“…An accuracy of up to 99.65% and 98.51% has been achieved on GREEND and UK-DALE data sets, respectively. While an accuracy of more than 96% has been attained on both WHITED and PLAID data sets. …”

Anonymizing multimedia documents by Haraty, Ramzi

“…A set of experiments are elaborated to demonstrate the efficiency of our technique.…”
Get full text
Get full text
Get full text
Get full text

BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”

Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

“…In total, 30 algorithms were used, with 19 appearing more than once. …”

Structural similarity evaluation between XML documents and DTDs by Tekli, J.

“…It is of polynomial complexity, in comparison with existing exponential algorithms. Classification experiments, conducted on large sets of real and synthetic XML documents, underline our approach effectiveness, as well as its applicability to large XML repositories and databases. © Springer-Verlag Berlin Heidelberg 2007.…”
Get full text
Get full text
Get full text
Get full text

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

“…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …”

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

“…<p dir="ltr">Electroencephalogram (EEG) signals suffer substantially from motion artifacts when recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. …”

Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges by Muhammad Mohsin Khan (22303366)

“…Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …”