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About

Dr. Salem A. Alyami is an Associate Professor in the Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University (IMSIU). He received his Master’s degree from King Saud University in 2008. He completed his PhD studies at Monash University in 2016. His research interests include applied statistics, biostatistics, mathematical statistics, simulation, Bayesian graphs, neural networks, Markov chain Monte Carlo methods, systems biology, modeling, learning causality, data mining, and signaling pathways. He has published more than 50 papers in influential journals.

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Skills

Experience

Organization
Assistant Professor

Imam Mohammad Ibn Saud Islamic University,

Dec-2022 to Present

Publication

  • dott image November, 2024

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

LandSin, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenit...

  • dott image November, 2024

A Novel Mixed Convolution Transformer Model for the Fast and Accurate Diagnosis of Glioma Subtypes

Glioblastoma is the most common adult brain tumor, significantly impacts disability and mortality. Early and accurate diagnosis of glioma subtypes is essential, but manual categorization is ...

  • dott image Alauddin Sabari
  • dott image November, 2024

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

LandSin, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenit...

  • dott image October, 2024

Multi-View Soft Attention-Based Model for the Classification of Lung Cancer-Associated Disabilities

Background: The detection of lung nodules at their early stages may significantly enhance the survival rate and prevent progression to severe disability caused by advanced lung cancer, but i...

  • dott image August, 2024

ASDNet: A robust involution-based architecture for diagnosis of autism spectrum disorder utilising eye-tracking technology

Journal : IET Computer Vision

Autism Spectrum Disorder (ASD) is a chronic condition characterised by impairments in social interaction and communication. Early detection of ASD is desired, and there exists a demand for t...

Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study

Sleep apnea (SA) is one of the most prevalent sleep-related problems, impacting more than 100 million people worldwide. A full-night Polysomnography (PSG) is an effective SA diagnosis strate...

An effective screening of COVID-19 pneumonia by employing chest X-ray segmentation and attention-based ensembled classification

Journal : IET Image Processing

Quick and accurate diagnosis of COVID-19 is crucial in preventing its transmission. Chest X-ray (CXR) imaging is often used for diagnosis, however, even experienced radiologists may misinter...

Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study

Sleep apnea (SA) is one of the most prevalent sleep-related problems, impacting more than 100 million people worldwide. A full-night Polysomnography (PSG) is an effective SA diagnosis strate...

  • dott image January, 2024

Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction

Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors and activit...

  • dott image January, 2024

Multi-Disease Detection Using a Prism-Based Surface Plasmon Resonance Sensor: A TMM and FEM Approach

Journal : IEEE Transactions on NanoBioscience

This research introduces a surface plasmon resonance (SPR)-based biosensor with multilayered structures for telecommunication wavelength in order to detect multiple diseases. The malaria and...