Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging by Maricar, Mohammed Farook

Get full text

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …”
Get full text
Get full text
Get full text

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System by Fahmida Haque (16896489)

“…<p dir="ltr">Diabetic sensorimotor polyneuropathy (DSPN) is an early indicator for non-healing diabetic wounds and diabetic foot ulcers, which account for one of the most common complications of diabetes, leading to increased healthcare cost, decreased quality of life, infections, amputations, and death. Early detection and intelligent classification tools for DSPN can allow correct diagnosis and treatment of painful diabetic neuropathy as well as a timely intervention to prevent foot ulceration, amputation, and other diabetic complications. …”

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

“…Correlation analysis provides several visualization features such as Kamada-Kawai, Fruchterman-Reingold Spring embedding network layouts, in addition to single circle, multiple circle and heatmap layouts, whereas comparative analysis presents expression-data distributions across samples, groups, and time points with boxplot display, outlier detection, and data curve fitting. BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”

SPA & MLST typing as epidemiological tools for the study of MRSA & MSSA Isolates in Lebanon. (c2009) by Rizk, Mazen

Get full text
Get full text

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…</p><h3>Objective</h3><p dir="ltr">This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes.…”

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

“…The use of AI in ECG analysis has several benefits, including the quick and precise detection of problems like arrhythmias, silent cardiac illnesses, and left ventricular failure. …”

Differential diagnosis of bile duct injury and ductopenia by West, A.B.

“…Moreover, although duct injury is generally easily detected in needle biopsy specimens, ductopenia is not infrequently both overlooked and overdiagnosed. …”
Get full text
Get full text
Get full text

Automatic image quality evaluation in digital radiography using for‐processing and for‐presentation images by Ioannis A. Tsalafoutas (14776939)

“…<h3>Purpose</h3><p dir="ltr">To investigate the impact of digital image post‐processing algorithms on various image quality (IQ) metrics of radiographic images under different exposure conditions.…”

Data Redundancy Management in Connected Environments by Mansour, Elio

“…We describe its modules, and clustering-based algorithms. Moreover, our proposal detects temporal, and spatial-temporal redundancies in order to consider both static and mobile devices/sensors. …”
Get full text
Get full text
Get full text
Get full text

A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics by Tekli, Joe

“…In this paper, we provide an integrated and fine-grained comparison framework to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and to allow the end-user to adjust the comparison process according to her requirements. …”
Get full text
Get full text
Get full text
Get full text

An XML Document Comparison Framework by Tekli, Joe

“…In this paper, we provide an integrated and fine-grained comparison method to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and allow the end-user to tune the comparison process according to her requirements. …”
Get full text
Get full text
Get full text

Approximate XML structure validation based on document–grammar tree similarity by Tekli, Joe

“…Results underline our approach’s effectiveness in classifying similar documents with respect to predefined grammars, accurately detecting document and/or grammar modifications, and performing document and grammar relevance ranking. …”
Get full text
Get full text
Get full text
Get full text

Approximate XML structure validation technical report by Tekli, Joe

“…Results underline our approach’s effectiveness in classifying similar documents with respect to predefined grammars, accuratly detecting document and/or grammar modifications, and performing document and grammar relevance ranking. …”
Get full text
Get full text
Get full text

UML-based regression testing for OO software by Mansour, Nashat

“…For the second phase, we present algorithms for detecting system level changes in the interaction overview diagram. …”
Get full text
Get full text
Get full text

Extreme Early Image Recognition Using Event-Based Vision by Abubakar Abubakar (18278998)

“…<p dir="ltr">While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. …”

Copy number variations in the genome of the Qatari population by Khalid A. Fakhro (3158862)

“…We present the first high-resolution copy number variation (CNV) map for a Gulf Arab population, using a hybrid approach that integrates array genotyping intensity data and next-generation sequencing reads to call CNVs in the Qatari population. CNVs were detected in 97 unrelated Qatari individuals by running two calling algorithms on each of two primary datasets: high-resolution genotyping (Illumina Omni 2.5M) and high depth whole-genome sequencing (Illumina PE 100bp). …”

Defined Clinical Classifications Are Associated with Outcome of Patients with Anatomically Resectable Pancreatic Adenocarcinoma Treated with Neoadjuvant Therapy by Tzeng, Ching-Wei

“…Results Resection rates for 138 CR, 41 BR-B, and 38 BR-C patients were 75, 46, and 37%, respectively (P < 0.001). Metastases, detected during treatment in 23% of patients, were the most common contraindication to resection among CR (15%) and BR-B (46%) patients. …”
Get full text
Get full text
Get full text

Artificial Intelligence and Machine Learning Applications in Sudden Cardiac Arrest Prediction and Management: A Comprehensive Review by Sarah Aqel (17787809)

“…Furthermore, the combination of AI with automated external defibrillators (AEDs) shows potential in better detecting shockable rhythms during cardiac arrest incidents.…”

A new method for broad‐scale modeling and projection of plant assemblages under climatic, biotic, and environmental cofiltering by Alessandro Ferrarini (3951098)

“…To this purpose, we first used multilabel algorithms in order to convert the task of explaining a large assemblage of plant communities into a classification framework able to capture with high cross-validated accuracy the pattern of species distributions under a composite set of biotic and abiotic factors. …”