title: Essentials of a robust deep learning system for diabetic retinopathy screening: A systematic literature review

authors: Chu, Aan

abstract: This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input.

text: Essentials of a robust deep learning system for diabetic retinopathy screening: A systematic literature review This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input.

year: 2020

title: Page turning and image size in a digital music stand

authors: Bell, Timothy C.

abstract: This paper investigates attributes of the electronic display of sheet music necessary for the development of a digital music stand. We explore the two conflicting goals of minimising page turning effort and maximising the readability of images by conducting two user experiments. In our first experiment participants trialed various page turning methods through a sight-reading exercise, and filled out a questionnaire upon completion. In the second experiment participants viewed music at different sizes while listening to an audio rendition of the piece, and were asked to note any mistakes that occured in the played audio. Results from our experimentations showed that scrolling techniques did not work as well as page replacement methods, and that some reduction in the size of the music displayed is possible without significantly degrading reader accuracy.

text: Page turning and image size in a digital music stand This paper investigates attributes of the electronic display of sheet music necessary for the development of a digital music stand. We explore the two conflicting goals of minimising page turning effort and maximising the readability of images by conducting two user experiments. In our first experiment participants trialed various page turning methods through a sight-reading exercise, and filled out a questionnaire upon completion. In the second experiment participants viewed music at different sizes while listening to an audio rendition of the piece, and were asked to note any mistakes that occured in the played audio. Results from our experimentations showed that scrolling techniques did not work as well as page replacement methods, and that some reduction in the size of the music displayed is possible without significantly degrading reader accuracy.

year: 2005

title: Obesity Management in Rural New Zealand General Practice from Healthcare Professional and Client Perspectives

authors: Norman, Kimberley

subjects: Obesity

abstract: Obesity is a health issue which currently affects over 34% of New Zealand (NZ) adults. Obesity, if left unchecked, leads to further physical and psychosocial health complications and an overall poor quality of life. People living in rural communities, high deprivation areas, as well as Indigenous Māori and Pacific Island populations in NZ, experience significant obesity health inequities and have a high-risk of developing obesity. General practice clinicians are positioned to be ‘best suited’ to deliver effective obesity healthcare in their practice, however, despite weight management intervention options being available through general practice, the obesity rates have continued to rise in the last 30 years. This suggests that there are potentially barriers to achieving a healthy weight in this context.
The aim of this research thesis is to understand the experiences with, and barriers to, effective obesity management in general practice from clinician and client perspectives to identify areas of improvement in the future.
This research thesis examines obesity healthcare in NZ general practice using a sequential explanatory mixed method research design in three parts. Firstly, a literature review study was conducted as a baseline point to identify the efficacy of any weight management interventions that are available in general practice. Secondly, a quantitative exploratory survey was conducted with Waikato region general practitioners (GP’s). Lastly, interviews with rural clinicians (GPs, nurses, and Indigenous Māori health professionals) and clients (patients engaging with rural general practice) were then conducted to understand the more in-depth perspectives of any barriers experienced with delivering, or engaging with, obesity management in general practice.
The experiences of both clinicians and clients were found to be complex and nuanced, with each participant having a unique experience with obesity management. Concepts such as effective yet inaccessible weight management interventions, interventions not suitable for sociocultural health needs, conflicting nutritional guidelines, lack of rural general practice systemic support, the unique and time consuming nature of obesity ‘treatment’, complications with the role of a clinician in obesity management, stigma or power imbalances in the general practice context, social determinants of health, the obesogenic environment, privatised weight management programmes and the individualised nature of sociocultural norms were found to be significant to effective obesity management.
This research thesis identified that the positioning of general practitioners as ‘best suited’ for delivering effective obesity healthcare in their practice was questionable. Potentially, the clinician role is better suited as a supportive one to an obesity health specialist who can meet the more holistic needs of a client when it comes to weight management. The current health model generates difficulties for clinicians to deliver comprehensive healthcare for such a complex and individualised health issue. Future research should look to develop weight management options that are suitable for rural and indigenous health needs to improve quality of life for clients and reduce health inequities. In addition, wider critical reflection on the current obesity healthcare model and the feasibility of a more specialist service outside general practice is warranted.

text: Obesity Management in Rural New Zealand General Practice from Healthcare Professional and Client Perspectives Obesity is a health issue which currently affects over 34% of New Zealand (NZ) adults. Obesity, if left unchecked, leads to further physical and psychosocial health complications and an overall poor quality of life. People living in rural communities, high deprivation areas, as well as Indigenous Māori and Pacific Island populations in NZ, experience significant obesity health inequities and have a high-risk of developing obesity. General practice clinicians are positioned to be ‘best suited’ to deliver effective obesity healthcare in their practice, however, despite weight management intervention options being available through general practice, the obesity rates have continued to rise in the last 30 years. This suggests that there are potentially barriers to achieving a healthy weight in this context.
The aim of this research thesis is to understand the experiences with, and barriers to, effective obesity management in general practice from clinician and client perspectives to identify areas of improvement in the future.
This research thesis examines obesity healthcare in NZ general practice using a sequential explanatory mixed method research design in three parts. Firstly, a literature review study was conducted as a baseline point to identify the efficacy of any weight management interventions that are available in general practice. Secondly, a quantitative exploratory survey was conducted with Waikato region general practitioners (GP’s). Lastly, interviews with rural clinicians (GPs, nurses, and Indigenous Māori health professionals) and clients (patients engaging with rural general practice) were then conducted to understand the more in-depth perspectives of any barriers experienced with delivering, or engaging with, obesity management in general practice.
The experiences of both clinicians and clients were found to be complex and nuanced, with each participant having a unique experience with obesity management. Concepts such as effective yet inaccessible weight management interventions, interventions not suitable for sociocultural health needs, conflicting nutritional guidelines, lack of rural general practice systemic support, the unique and time consuming nature of obesity ‘treatment’, complications with the role of a clinician in obesity management, stigma or power imbalances in the general practice context, social determinants of health, the obesogenic environment, privatised weight management programmes and the individualised nature of sociocultural norms were found to be significant to effective obesity management.
This research thesis identified that the positioning of general practitioners as ‘best suited’ for delivering effective obesity healthcare in their practice was questionable. Potentially, the clinician role is better suited as a supportive one to an obesity health specialist who can meet the more holistic needs of a client when it comes to weight management. The current health model generates difficulties for clinicians to deliver comprehensive healthcare for such a complex and individualised health issue. Future research should look to develop weight management options that are suitable for rural and indigenous health needs to improve quality of life for clients and reduce health inequities. In addition, wider critical reflection on the current obesity healthcare model and the feasibility of a more specialist service outside general practice is warranted.

year: 2024