Dr. Abdulrahman Nasser Mohammed Al Mubti

ِAssistant Professor

PhD in Computed Tomography
College of Applied Medical Sciences
Department of Radiological Sciences

A lecturer and researcher in Radiological Sciences with expertise in medical imaging, radiomics, and machine-learning applications in oncology. Experienced in CT and MRI systems, academic teaching, and interdisciplinary research. Committed to advancing diagnostic radiology through innovation and collaboration.

0175417574
analmopti@nu.edu.sa

المؤهلات العلمية

  • PhD (Medicine) – University of Dundee, United Kingdom (June 2025)

  • MSc in Medical Imaging – University of Manchester, United Kingdom (November 2019)

  • BSc in Diagnostic Radiography – King Khalid University, Saudi Arabia (August 2012)

الخبرات

Lecturer, Department of Radiological Sciences, Najran University (2012 – Present)

التخصصات والمهارات

Diagnostic Medical Imaging

CT (16/64-slice) and MRI

Radiomics and Image Texture Analysis

Radiomics and texture feature analysis

Predictive Modeling

Tumor predictive modeling (UTUC, RCC) and cardiac index measurements

الدورات التدربية

Introduction to Good Clinical Practice (ICH E6 GCP)

  • Provider: NHS Research Scotland (NRS)

  • Dates: 25 Oct 2022 and 26 Apr 2023

  • Topics: history of clinical trials and GCP development; GCP principles; UK legislation (Statutory Instrument); informed consent; responsibilities of investigator and sponsor; study conduct; safety reporting; trial files (TMF/ISF) and data management; QA/QC and monitoring.

Introduction to R for Data Analysis

  • Instructor: Dr. Andrew Miles

  • Dates: 12–15 Mar 2025

Human Tissue Governance

  • Program: Guided training session – TASC

  • Location: Ninewells Hospital and Medical School

  • Date: 6 Dec 2023

PGR Research Integrity Training Resource

  • Provider: University of Dundee

  • Academic Year: 2022/2023

Essential Documents in Clinical Research

  • Provider: Tayside Medical Science Centre

  • Location: Ninewells Hospital and Medical School

  • Date: 13 Sep 2023

Principles of Artificial Intelligence

  • Provider: Saudi Data & AI Authority (SDAIA)

  • Date: Oct 2025

  • Content: overview of AI concepts, machine learning, and intelligent decision-making models in medical applications.

Concepts and Advanced Applications of Artificial Intelligence

  • Provider: Saudi Data & AI Authority (SDAIA)

  • Date: Oct 2025

  • Content: advanced AI concepts, deep learning, and AI use in medical image analysis to improve diagnostic accuracy.

Scientific Publications

Al Mopti, A., Alqahtani, A., Alshehri, A.H.D., Li, C., Nabi, G. (2025). Evaluating the Predictive Capability of Radiomics Features of Perirenal Fat in Enhanced CT Images for Staging and Grading of UTUC Tumours Using Machine Learning. Cancers, 17(7), 1220.
Al Mopti, A., Alqahtani, A., Alshehri, A.H.D., Li, C., Nabi, G. (2024). Perirenal Fat CT Radiomics-Based Survival Model for Upper Tract Urothelial Carcinoma: Integrating Texture Features with Clinical Predictors. Cancers, 16, 3772.
Alqahtani, A., Bhattacharjee, S., Almopti, A., Li, C., Nabi, G. (2024). Radiomics-based machine learning approach for predicting grade and stage in upper tract urothelial carcinoma: a step towards virtual biopsy. International Journal of Surgery, 110(6), 3258–68.
Alqahtani, A., Bhattacharjee, S., Almopti, A., Li, C., Nabi, G. (2024). Radiomics-based computed tomography urogram approach for the prediction of survival and recurrence in upper tract urothelial carcinoma. Cancers, 16(18), 3119.

 

Taught Courses

Computed Tomography Technology (RAD-3 427)

Applied Pathology (RAD-2 458)

Radiologic Pathology (RAD-2 341)

Office Hours

 

  8-9 9-10 10-11 11-12 12-1 1-2
الأحد
Sunday		            
الاثنين
Monday		 Office Hours Office Hours Office Hours      
الثلاثاء
Tuesday		         Office Hours  
الأربعاء
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الخميس
Thursday		 Office Hours