Daniel Al MouieeIngham Institute · Department of Medical Physics
Daniel Al Mouiee
B.Software Engineering / M.Biomedical Engineering
Radiotherapy Computer Scientist @ Ingham Institute & PhD Student @ UNSW
About
10
Publications
357
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
9
Citations
Introduction
Skills and Expertise
Additional affiliations
December 2020 - present
Position
- Researcher
Description
- My role involves developing tools to optimise radiation therapy clinical procedures at the South Western Sydney Local Health District. I also assist and contribute to radiation therapy and medical physics research projects that involve image processing, computer vision and deep learning.
September 2019 - December 2020
Position
- Research Associate
Description
- Contributing to the development of advanced machine-learning methods and deep-learning models that leverage large omics data to find hidden structures within them, account for complex interactions among the measurements, integrate heterogeneous data and make accurate predictions in different biomedical applications.
Education
January 2016 - December 2020
Publications
Publications (10)
Multiple outcome prediction models have been developed for Head and Neck Squamous Cell Carcinoma (HNSCC). This systematic review aimed to identify HNSCC outcome prediction model studies, assess their methodological quality and identify those with potential utility for clinical practice. Inclusion criteria were mucosal HNSCC prognostic prediction mo...
In progressing the use of big data in health systems, standardised nomenclature is required to enable data pooling and analyses. In many radiotherapy planning systems and their data archives, target volumes (TV) and organ-at-risk (OAR) structure nomenclature has not been standardised. Machine learning (ML) has been utilised to standardise volumes n...
In progressing the use of big data in health systems, standardised nomenclature is required to enable data pooling and analyses. In many radiotherapy planning systems and their data archives, target volumes (TV) and organ-at-risk (OAR) structure nomenclature has not been standardised. Machine learning (ML) have been utilized to standardise volumes...
Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen often adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expres...
Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression i...
Purpose:
Artificial intelligence (AI) techniques are increasingly being used to classify retinal diseases. In this study we investigated the ability of a convolutional neural network (CNN) in categorizing histological images into different classes of retinal degeneration.
Methods:
Images were obtained from a chemically induced feline model of mo...
