Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems حسب Mahmood, Lubna Syeda

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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب Arfan Ahmed (17541309)

"…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …"

Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability حسب Farah R. Zahir (18892108)

"…The <i>de novo</i> assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation.…"

Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review حسب Hiba Alzoubi (18001609)

"…</p><h3>Objective</h3><p dir="ltr">This systematic review evaluates the performance of AI models in detecting and subtyping medulloblastomas using histopathological images. </p><h3>Methods</h3><p dir="ltr">In this systematic review, we searched seven databases to identify English-language studies assessing AI-based detection or classification of medulloblastomas in patients under 18 years. …"

BioNetApp: An interactive visual data analysis platform for molecular expressions حسب 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.…"

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications حسب Abdallah Falah Mohammad Aldwekat (22457821)

"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"