Artificial intelligence methodologies and their application to diabetes

In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers?doctors and nurses?in this field

Scientific advances in diabetes: the impact of the innovative medicines initiative

Tese de mestrado, Regulação e Avaliação do Medicamento e Produtos de Saúde, 2020, Universidade de Lisboa, Faculdade de Farmácia.A Iniciativa sobre Medicamentos Inovadores é uma parceria público-privada entre a Comunidade Europeia, representada pela Comissão Europeia, e a Indústria Farmacêutica, representada pela Federação Europeia da Indústria Farmacêutica. Esta Iniciativa de Tecnologia Conjunta tem como objetivos acelerar o processo de investigação e desenvolvimento de medicamentos inovadores, bem como gerar novos conhecimentos científicos que promovam a integração da medicina personalizada nas doenças prioritárias definidas pela Organização Mundial de Saúde. Atualmente, no âmbito desta iniciativa foram estabelecidos dois programas, sendo que o primeiro (IMI1) decorreu entre 2008 e 2013 e teve um orçamento de 2 mil milhões de euros, enquanto que o segundo programa (IMI2) está em decurso desde 2014 e terminará em 2020 e o orçamento disponibilizado foi de 3.276 mil milhões de euros. A diabetes mellitus é uma das doenças prioritárias indicadas pela Organização Mundial de Saúde alvo de financiamento pelos programas IMI. As principais justificações para este facto prendem-se com os dados epidemiológicos da doença. No decorrer dos anos, verificou-se um aumento exponencial da taxa de prevalência desta doença a nível mundial. Esta evidência é suportada pelo facto de, entre o período de 1980 e 2014, esta taxa ter sofrido um aumento de 4.7% para 8.7%, o quadruplo do valor, em adultos com idade igual ou superior a 18 anos e também por as estimativas a 20 anos, realizadas pela Organização Mundial de Saúde, indicarem que o número total de casos existentes corresponderá a mais de 20% da população universal. Simultaneamente, constatou-se um crescimento progressivo tanto da taxa de mortalidade por diabetes bem como dos custos de saúde acarretados por esta doença. No que diz respeito à taxa de mortalidade, em 2016, a diabetes foi considerada a sétima principal causa de morte no mundo. Em termos de impacto económico, a diabetes e as complicações decorrentes desta doença, como é o caso das doenças cardiovasculares, nefropatia diabética e retinopatia diabética, impõem um grande peso económico para os sistemas de saúde. A nível mundial, os custos anuais provocados pela diabetes, entre o ano de 2007 e 2019, aumentaram de 232 mil milhões de dólares para 760 mil milhões de dólares, o que equivale a incremento de 528 mil milhões de dólares em 12 anos. Na área da Diabetes, o principal objetivo dos programas IMI1 e IMI2 é o de reduzir a tendência crescente observada na taxa de prevalência desta doença. De forma a atingir esta meta, os dois programas supramencionados primaram o financiamento de projetos cujo intuito consistia no desenvolvimento do conhecimento, medicamentos, métodos, ferramentas e modelos que facilitassem a implementação da medicina personalizada, como modelo de prática médica corrente, em doentes com diabetes. Até outubro de 2019, os programas IMI financiaram treze projetos para a área da Diabetes & Doenças Metabólicas, nomeadamente SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT e CARDIATEAM. Entre estes, o INNODIA tinha como objetivo a diabetes tipo 1, o DIRECT, EMIF e RHAPSODY tinham como foco a diabetes tipo 2, o SUMMIT, BEAT-DKD, LITMUS, Hypo-RESOLVE e CARDIATEAM estavam associados às complicações da diabetes e os restantes projetos, o StemBANCC, EBiSC, IMIDIA e IMI2PACT, estavam orientados para o desenvolvimento da vertente científica. Em geral, um investimento monetário total na ordem dos €447 249 438 foi realizado pelo IMI na área da Diabetes. Todavia, a deteção da lacuna existente na integração dos resultados produzidos pelos diferentes projetos, impulsionou a elaboração da presente dissertação intitulada de “Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative”, ou seja, Avanços Científicos na Área da Diabetes: Impacto da Iniciativa sobre Medicamentos Inovadores. Os principais objetivos estabelecidos para esta dissertação foram os de recolher os artigos publicados pelos projetos financiados e sistematizá-los nos eixos de investigação definidos na agenda estratégica do programa IMI2, mais concretamente: 1) identificação de alvos e biomarcadores, 2) novos paradigmas de ensaios clínicos, 3) medicamentos inovadores e 4) programas de adesão terapêutica centrados nos doentes. A metodologia de investigação aplicada nesta dissertação consistiu numa revisão de literatura, tendo-se utilizado como fontes de dados as páginas eletrónicas oficiais de cada projeto, o contacto com os coordenadores e co-coordenadores dos projetos e a base de dados europeia Cordis. No geral, um total de 662 citações foram identificadas, das quais 185 foram incluídas na análise realizada neste trabalho. Através da sistematização e integração dos artigos recolhidos nos projetos financiados pelo IMI, averiguou-se que para o eixo de identificação de alvos e biomarcadores, os outcomes relevantes responderam a cinco das recomendações definidas na agenda estratégica do programa IMI2, nomeadamente: 1) identificar e validar marcadores biológicos, ferramentas e ensaios, 2) identificar as determinantes que justificam a variabilidade interindividual, 3) compreender os mecanismos moleculares subjacentes à doença, 4) desenvolver uma plataforma de ensaios pré-clínicos e 5) estabelecer modelos de sistemas. De um modo geral, um vasto número de biomarcadores, ferramentas, fatores responsáveis pela heterogeneidade da população, incluindo marcadores genéticos, e mecanismos relevantes foram identificados para a diabetes tipo 1 pelo INNODIA, para a diabetes tipo 2 pelo SUMMIT, IMIDIA, DIRECT e EMIF, para as células beta pancreáticas pelo IMIDIA e RHAPSODY, para a nefropatia diabética pelo SUMMIT e BEAT-DKD, e para as doenças cardiovasculares e retinopatia diabética pelo SUMMIT. Suplementarmente, um conjunto de ferramentas e ensaios foram desenvolvidos pelos projetos StemBANCC, EBiSC e IMIDIA com o intuito de impulsionar avanços na área investigacional. Ainda neste eixo foram propostos dois modelos de estratificação dos doentes, um relativo ao controlo glicémico em doentes com diabetes tipo 1 estabelecido pelo INNODIA e outro correspondente à identificação dos subtipos de doentes com diabetes desenvolvido pela parceria BEAT-DKD/RHAPSODY. Relativamente ao eixo de ensaios clínicos, os dados analisados compreendiam propostas de novos parâmetros clínicos e de desenhos de ensaios, sendo que estes resultados visavam espelharem com maior precisão as características da subpopulação com diabetes em teste. Os dados incluídos neste eixo foram obtidos a partir dos projetos SUMMIT, DIRECT e BEAT-DKD. No que concerne ao eixo de medicamentos inovadores, as informações recolhidas dos artigos publicados pelos projetos SUMMIT, IMIDIA, DIRECT, StemBANNC, EMIF, INNODIA e BEAT-DKD consistiam na identificação de novos potenciais alvos terapêuticos bem como no desenvolvimento de novos agentes terapêuticos, ambos com a finalidade de tratar ou prevenir tanto a diabetes como as complicações associadas a esta doença. Foi ainda proposta uma nova abordagem de produção de células estaminais pluripotentes humanas em larga escala pelo StemBANCC. No que tange aos programas de maximização de resultados de saúde benéficos centrados no doente com diabetes, dois novos modelos preditivos foram desenvolvidos e validados pelo projeto DIRECT, permitindo a sua utilização como ferramentas de diagnóstico por médicos especialistas. Adicionalmente, esta dissertação tem como objetivo apresentar uma proposta de visão de complementaridade entre os treze projetos financiados pelo IMI, realçando as possíveis estratégias a adotar para a integração da medicina personalizada na prática clínica. Esta abordagem engloba a criação de indicadores biológicos e genéticos que facilitem a identificação dos indivíduos com risco elevado de desenvolver diabetes, a inclusão de ferramentas que possibilitem o diagnóstico precoce dos doentes e, por último, a seleção do tratamento apropriado às características do indivíduo, ou seja o que evidencie ser mais eficaz e seguro, suportado em modelos de estratificação de doentes, tentando desta forma retardar a progressão da doença, assim como prevenir o desenvolvimento das complicações relacionadas com a progressão da doença.Innovative Medicines Initiative (IMI) is a public-private partnership between the European Community, represented by the European Commission, and the European Federation of Pharmaceutical Industries and Associations. This joint undertaking aims at accelerating the medicines development process and generating new scientific knowledge to promote the implementation of personalized medicine for priority diseases established by the World Health Organization. Currently, two IMI programmes have been undertaken, the first one (IMI1) was carried out from 2008 until 2013 and had a budget of €2 billion, and the second one (IMI2) was developed from 2014 up to 2020 and the budget committed was up to €3.276 billion. Diabetes Mellitus is one of the World Health Organization’s priority diseases under research by the IMI programmes, mainly due to the exponential increase of its global prevalence over the years. Between 1980 and 2014, this rate quadrupled from 4.7% to 8.7% in adults aged 18 years and older and the 20 years- World Health Organization’s projections indicate that it could reach more than 20% of the population. Simultaneously, the mortality rate and the healthcare costs associated with diabetes have been increasing. Regarding mortality, diabetes was the seventh leading cause of death in 2016. In terms of economic impact, currently, diabetes and its related complications, such as cardiovascular diseases, diabetic kidney disease and diabetic retinopathy, represent a significant economic burden on the healthcare systems. Worldwide, the estimated annual costs of diabetes have increased from $232 billion to$760 billion, between 2007 and 2019. In the Diabetes field, the main aim of IMI1 and IMI2 programmes is to shorten the prevalence of this disease, through the development of knowledge and methods that enable the implementation of personalized treatment for diabetic patients. Up to October of 2019, thirteen projects were funded by IMI for Diabetes & Metabolic disorders, more precisely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. Of these, INNODIA aimed at type 1 diabetes, DIRECT, EMIF and RHAPSODY were focused on type 2 diabetes, SUMMIT, BEAT-DKD, LITMUS, Hypo- RESOLVE and CARDIATEAM were related to complications of diabetes, and the remaining projects, namely StemBANCC, EBiSC, IMIDIA and IMI2PACT, were directed to scientific research. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. However, there is a substantial lack of integration of achievements between the different projects, which prompted the development of this dissertation: “Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative”. This dissertation’ objectives were to collect the data of the funded-projects and integrate them into the following research axes: 1) target and biomarker identification, 2) innovative clinical trials paradigms, 3) innovative medicines, and 4) patient-tailored adherence programmes. The research methodology applied was a literature review and the data sources used were the official project’s websites, contacts with the project’s coordinators and co-coordinator and the CORDIS database. From the 662 citations identified, 185 were included. Through the integration of the data collected from IMI-funded projects, it was verified that for Target and Biomarker identification, the main achievements were in order to 1) identify and validate biological markers, tools and assays, 2) identify determinants of inter-individual variability, 3) understand the molecular mechanisms underlying the disease, 4) develop a platform of pre-clinical assays, and 5) develop systems’ models. Therefore, several biomarkers, tools, inter-individual variability factors, including genetic markers, and relevant pathways were proposed for type 1 diabetes by INNODIA, for type 2 diabetes by SUMMIT, IMIDIA, DIRECT and EMIF, for pancreatic β-cells by IMIDIA and RHAPSODY, for diabetic kidney disease by SUMMIT and BEAT-DKD, and for cardiovascular diseases and diabetic retinopathy by SUMMIT. Moreover, new tools and assays to improve research field were developed by StemBANCC, EBiSC and IMIDIA. Also, two models for patients’ stratification were proposed, one related to glycaemic control in patients with type 1 diabetes established by INNODIA, and another corresponding to the identification of subtypes of diabetes patients developed by BEAT-DKD/RHAPSODY. Regarding the clinical trials, the data collected SUMMIT, DIRECT and BEAT-DKD corresponds to new clinical endpoints and trial designs to accurately reflect the characteristics of the diabetic subpopulation under test. In terms of innovative medicines, information retrieved by SUMMIT, IMIDIA, DIRECT, StemBANNC, EMIF, INNODIA and BEAT-DKD consists on the identification of new therapeutic targets and the development of agents with the purpose of treatment and prevent diabetes and its related complications. Furthermore, a new approach for the large-scale production of human pluripotent stem cells was proposed by StemBANCC. Concerning the maximization of beneficial health patient-centred outcomes, two novel predictive models were developed and validated by DIRECT for diabetes to be used as screening tools by doctors. In addition, this dissertation intends to present a joint vision of the IMI-projects with strategies for integrating personalized medicine into healthcare practice. This approach involves the creation of biological and genetic indicators that can be used to identify individuals at high risk of developing diabetes, the adoption of tools that allow early diagnosis and, lastly, the selection of appropriate treatment, i.e. the safest and most effective, supported by patient stratification models, in order to prevent/delay the development of diabetic complications

Basal-Bolus Advisor for Type 1 Diabetes (T1D) Patients Using Multi-Agent Reinforcement Learning (RL) Methodology

This paper presents a novel multi-agent reinforcement learning (RL) approach for personalized glucose control in individuals with type 1 diabetes (T1D). The method employs a closed-loop system consisting of a blood glucose (BG) metabolic model and a multi-agent soft actor-critic RL model acting as the basal-bolus advisor. Performance evaluation is conducted in three scenarios, comparing the RL agents to conventional therapy. Evaluation metrics include glucose levels (minimum, maximum, and mean), time spent in different BG ranges, and average daily bolus and basal insulin dosages. Results demonstrate that the RL-based basal-bolus advisor significantly improves glucose control, reducing glycemic variability and increasing time spent within the target range (70-180 mg/dL). Hypoglycemia events are effectively prevented, and severe hyperglycemia events are reduced. The RL approach also leads to a statistically significant reduction in average daily basal insulin dosage compared to conventional therapy. These findings highlight the effectiveness of the multi-agent RL approach in achieving better glucose control and mitigating the risk of severe hyperglycemia in individuals with T1D.Comment: 8 pages, 2 figures, 1 Tabl

From bench to bedside: Tracing the payback forwards from basic or early clinical research – A preliminary exercise and proposals for a future study

EXECUTIVE SUMMARY Chapter 1 : Introduction • The members of the research team from HERG and the Wellcome Trust have conducted previous studies showing that it is possible both to assess the payback from applied health research, and to use bibliometrics to trace the links between generations of research and clinical guidelines. In another of the team’s studies, however, it proved difficult to replicate the major study by Comroe and Dripps (1976) that had identified clinical advances and then worked backwards to show that they had relied on earlier basic research. Therefore, the study reported here sets out to use the methods developed in our previous studies of payback to undertake analysis that starts with more basic or early clinical research and traces the research lines forwards to clinical applications. Whilst this preliminary study involved preparation for a future large-scale study, it was hoped that it would also provide an interesting case study. • Starting with the research outputs of one team 20 years ago, called the 1st generation papers, the preliminary study has three main elements: standard bibliometric analysis through several generations of papers; categorisation of the citations; and qualitative analysis using questionnaires, critical pathway analysis and interviews to trace the impact of the 1st generation of research. • Diabetes and cardiology were suggested as possible topics on which to base the study. Initial reviews identified two bodies of research in diabetes as being potentially suitable for reasons such as the continuing activity of key members of the team. • The research into diabetes conducted in 1981 by George Alberti and his team at Newcastle, and collaborators elsewhere, was selected to provide the case study for this preliminary stage for several reasons. It was thought to have been important science and there was a belief that some of it had made a contribution to clinical practice. Chapter 2 : Bibliometric analysis • An original plan to look at publications produced over a three year period was changed to looking at the output of just one year, 1981, because in that year alone Alberti and colleagues published 29 articles. These form the 1st generation papers and the average number of citations they received is high. Identifying the citations given to these 29 papers resulted in 799 2nd generation papers and 12,891 3rd generation papers. The numbers involved meant that it was impractical to go beyond the 3rd generation. Within the high overall average, the variation in the number of citations per paper was iii considerable going from 76 to just one. Similarly, the half-lives of the 29 papers, ie the time taken for an article to receive 50% of its citations, ranged from two years to 11. • Articles can be given a Research Level (ie one of four levels from clinical observation to basic) based on the journals in which they appear. Such analysis demonstrates the breadth of Alberti’s work because the 29 articles are spread across all four Research Levels. Crucially, there was not a shift from basic to more clinical levels across the generations. The higher than average number of authors and addresses per paper is testimony to Alberti’s extensive collaborations. • The funding acknowledgements reveal the high proportion of papers supported, at least partially, by one funder: the British Diabetic Association, now Diabetes UK, which provided core support for Alberti’s Newcastle team. Chapter 3 : Categorisation of citations • Traditional citation analysis does not allow identification of the importance of the cited article to the citing article, and therefore limits the ability to use citation analysis to trace the impact of basic or early research on later research. We conducted a review of the literature of the meaning of citations. • From this review, a template was devised that allowed the location, nature and importance of citations to be recorded as well as the type of research (basic or clinical) described in the paper. This was used by six assessors on a sample of papers and inter-rater reliability was tested. Further work is required to refine the template and its definitions, and to improve its consistency in application. • Nevertheless, for initial analysis, it was applied to 623 out of the 799 2nd generation papers. A four point scale was used for the importance of the cited paper to the citing paper. In just 9% of cases was the cited 1st generation paper thought to be in one of the top two categories, ie of Considerable or Essential importance to the citing paper. • Statistical analysis revealed no relationship between the number of citations a paper received and the proportion of citations where the cited paper was classified as being of high (ie. Considerable or Essential) importance to the citing paper. Self-citations, however, were shown to be significantly more likely to be in this category. • The classification of the type of research (basic or clinical) by our analysis of each paper broadly agreed with the classification of the journals by Research Level. • The time constraints involved in applying the template, plus the lack of any overall pattern in terms of correlations between number and importance of citations, might point to the desirability of adopting a more selective approach, guided by qualitative analysis. In any selective approach, however, it is likely that self-citations should feature. iv Chapter 4 : Qualitative analysis • Given the number of co-authors, it seemed appropriate to send them a questionnaire rather than attempt to interview them. Therefore the interviewing was rather more concentrated than originally intended. Only one formal critical pathway was created, but it was undertaken by an expert in the field who worked with Alberti at Newcastle. • Some problems emerged in taking 1981 as the starting point for the study. Alberti identified 10 selected papers from the 1970s and 1980s that he felt had had most impact on clinical practice. These helped to give us both a better understanding of the payback from our 1st generation, or 1981, papers, and provided further material for analysis. • Attempting to describe the impact from the 1981 body of work, and from the 10 selected papers, underlines the complex reality of how science advances and influences clinical practice. If they make a contribution at all, most studies make a small, incremental one. • A few papers, however, have been shown to have a considerably greater impact. A possible key to the level of payback indicated is the enormous breadth of Alberti’s contacts, and fields and methods of working, to which various references were made. This is well illustrated in the account of how the idea for subcutaneous pumps came about. Similarly, the ability to produce the very important guidelines on treating diabetics during surgery, and diabetic coma, partly resulted from the application to clinical problems of the understandings gained from some of the basic/early clinical studies. It is significant that the key papers on these issues, all of which come from the list of 10 selected papers from the 1970s and 1980s, were having an impact on the 1981 work. • How far the collection of papers from 1981 have been drawn upon in similar ways is less clear. Nevertheless, papers on treating diabetics during open heart surgery, and on bolus delivery of insulin at meal times, were key parts of these wider streams, despite variable citation levels. Furthermore, various papers, including on acarbose, on portal infusion of insulin, and on semi-human insulin, were important steps in bodies of work in their respective areas. The complexity was illustrated by a paper that helped debunk the Chlorpropamide alcohol flushing hypothesis, and thus end a line of scientific enquiry: there was payback in stopping an incorrect line of inquiry, but nothing on which to build. • Each technique in the qualitative study produced information about the successful subsequent careers followed by many researchers trained through working with Alberti. • Historical perspectives, and insider expert opinions, were important in the qualitative analysis. Overall, the qualitative methods highlighted some limitations in the bibliometric approach but also showed how aspects of the citation analysis can complement the opinions expressed, for example about the importance of the breadth of Alberti’s work. v Chapter 5 : Lessons learnt and the way forward • Lessons learnt: a variety of methods can be used successfully to gather considerable data about the payback from a body of research undertaken 20 years ago. Traditional citation analysis alone, however, is not sufficient: the importance of the surgery papers despite their relatively low citation rates illustrates this. The qualitative methods are important and much of the analysis is strengthened by drawing on multiple approaches. Several problems remain, including: identifying a coherent starting point for the analysis; coping with the enormous number of papers involved in later generations; and refining the template for categorising citations and developing ways of fully utilising the results from applying it. • Preparing for the large-scale study: this preliminary study provides a basis on which to attempt to undertake the larger study we envisaged. Issues now being addressed include identification of the level of bibliometric/citation analysis necessary to complement any qualitative studies. To provide confidence in the findings from an eventual large-scale study, we will need to expand the focus. The study will need to cover at least four sets of case studies. Ideally, each set should focus on a number of research groups working in a country in the same field. We hope there will be sets of case studies in two or three fields and in at least two countries. The issues to be explored will include ones highlighted by this study such as breadth of work, level of collaboration, and the role of core funding. • Methods for the large-scale study: for each case study we now propose to employ two methodological elements based on the qualitative and quantitative techniques adopted in the preliminary study. They will work in parallel but the quantitative bibliometric analysis would be applied selectively to parts of ‘research lines’ (ie discrete themes of research) identified in the qualitative studies as being important in influencing clinical practice. • Presenting the findings: each research line could be written-up in a standardised document that would use the HERG payback model and categories to describe the impact of that research. We shall use the qualitative and quantitative data to compare and contrast the ‘payback’ of research lines by country and disease, and then identify common factors that correlate with the translation of basic or early clinical research. • Concluding comments: in the era of ‘evidence based policy’, research funders are looking for value for money in the research they support and for evidence on the effectiveness of different research strategies. In this study we have begun developing a methodology that will allow us to understand the complexity of research development over a series of generations. The utility of the policy research we propose here will only be realised when it is scaled up to cover a number of different fields in different settings.NHS Executive, London Regio

Emerging Treatment Strategies for Diabetes Mellitus and Associated Complications: An Update

The occurrence of diabetes mellitus (DM) is increasing rapidly at an accelerating rate worldwide. The status of diabetes has changed over the last three generations; whereas before it was deemed a minor disease of older people but currently it is now one of the leading causes of morbidity and mortality among middle-aged and young people. High blood glucose-mediated functional loss, insulin sensitivity, and insulin deficiency lead to chronic disorders such as Type 1 and Type 2 DM. Traditional treatments of DM, such as insulin sensitization and insulin secretion cause undesirable side effects, leading to patient incompliance and lack of treatment. Nanotechnology in diabetes studies has encouraged the development of new modalities for measuring glucose and supplying insulin that hold the potential to improve the quality of life of diabetics. Other therapies, such as β-cells regeneration and gene therapy, in addition to insulin and oral hypoglycemic drugs, are currently used to control diabetes. The present review highlights the nanocarrier-based drug delivery systems and emerging treatment strategies of DM

Diabetes Diagnosis by Case-Based Reasoning and Fuzzy Logic

In the medical field, experts’ knowledge is based on experience, theoretical knowledge and rules. Case-based reasoning is a problem-solving paradigm which is based on past experiences. For this purpose, a large number of decision support applications based on CBR have been developed. Cases retrieval is often considered as the most important step of case-based reasoning. In this article, we integrate fuzzy logic and data mining to improve the response time and the accuracy of the retrieval of similar cases. The proposed Fuzzy CBR is composed of two complementary parts; the part of classification by fuzzy decision tree realized by Fispro and the part of case-based reasoning realized by the platform JColibri. The use of fuzzy logic aims to reduce the complexity of calculating the degree of similarity that can exist between diabetic patients who require different monitoring plans. The results of the proposed approach are compared with earlier methods using accuracy as metrics. The experimental results indicate that the fuzzy decision tree is very effective in improving the accuracy for diabetes classification and hence improving the retrieval step of CBR reasoning

A literature review for nurses on the potential diabetic complications in children and young adults

The incidence of Insulin Dependent Diabetes Mellitus (IDDM) in childhood is increasing within the United Kingdom. Prior to the discovery of Insulin in 1922, patients with IDDM died and although treatment with daily insulin injections is now effective in the everyday control of the disease, it does not prevent the individual from developing the long-term complications associated with the metabolic disorder. The majority of research into childhood diabetes and the potential problems due to complications is carried out within the medical field. Although this research is valuable it rarely approaches the problems of diabetes from a nursing perspective. There is however literature available in a number of journals that is written from the nursing point of view encompassing a range of diabetes related topics. The purpose of this dissertation is to review the limited literature found and present the conclusions in a concise and readable form. The history of diabetes is described emphasising the fact that insulin therapy is still a relatively new treatment. The long and short-term complications associated with diabetes are defined in order that the articles reviewed later in the dissertation can be understood. The methodology of the literature search is discussed and reasons are given for focusing on certain themes that were then further expanded in the review chapters. The conclusion focuses on the themes that developed such as the need for education, compliance, new developments in treatment, glycaemic control and the role of the Paediatric Diabetes Specialist Nurse. It is hoped that the dissertation will encourage the reader to utilise this information in the provision of care to young people who are affected by IDDM. The information available from the whole range of the media, including the Internet, is examined and the difficulty that the quality of this information can pose to health care professionals is discussed. The implications for research based nursing practice are explored and ideas for potential research projects as a result of the themes described are suggested