Biomedical time series analysis based on bag-of-words model

This research proposes a number of new methods for biomedical time series classification and clustering based on a novel Bag-of-Words (BoW) representation. It is anticipated that the objective and automatic biomedical time series clustering and classification technologies developed in this work will potentially benefit a wide range of applications, such as biomedical data management, archiving, retrieving, and disease diagnosis and prognosis in the future

COHORT IDENTIFICATION FROM FREE-TEXT CLINICAL NOTES USING SNOMED CT’S SEMANTIC RELATIONS

In this paper, a new cohort identification framework that exploits the semantic hierarchy of SNOMED CT is proposed to overcome the limitations of supervised machine learning-based approaches. Eligibility criteria descriptions and free-text clinical notes from the 2018 National NLP Clinical Challenge (n2c2) were processed to map to relevant SNOMED CT concepts and to measure semantic similarity between the eligibility criteria and patients. The eligibility of a patient was determined if the patient had a similarity score higher than a threshold cut-off value, which was established where the best F1 score could be achieved. The performance of the proposed system was evaluated for three eligibility criteria. The current framework’s macro-average F1 score across three eligibility criteria was higher than the previously reported results of the 2018 n2c2 (0.933 vs. 0.889). This study demonstrated that SNOMED CT alone can be leveraged for cohort identification tasks without referring to external textual sources for training.Doctor of Philosoph

Computational study of therapeutic targets and ADME-Associated proteins and application in drug design

Ph.DDOCTOR OF PHILOSOPH

Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain

Hypoglycaemia in Diabetes and Dementia Population

BACKGROUND: Diabetes mellitus (DM) and dementia are common long-term conditions that co-exist in a large proportion of the elderly. Diabetic patients with dementia may be less able to self-manage and control their diabetes, placing them at a higher risk of complications such as hypoglycaemia. AIM: This thesis aimed to investigate the risk of hypoglycaemia associated with dementia diagnosis among patients with DM. METHODS: This thesis describes work conducted using The IQVIA Medical Research Data (IMRD)‐UK database. Firstly, a descriptive, population-based study was conducted to estimate the prevalence and incidence of dementia in the diabetes population. Secondly, a descriptive, drug utilisation study was conducted to describe the prescribing pattern of antidiabetic medications and the rate of hypoglycaemia. Thirdly, a cohort study was conducted to investigate the association between dementia diagnosis and hypoglycaemia among patients with DM. Finally, a retrospective, pre-post exposure study was conducted to explore the glycaemic control and the rate of hypoglycaemia in diabetes patients pre- and post-dementia diagnosis. RESULTS: There was a trend of increasing prevalence and incidence of dementia, annual antidiabetic medication prescribing and hypoglycaemia rate in patients diagnosed with both DM and dementia over the period of 2000–2016. Patients diagnosed with dementia were at a twofold increased risk for hypoglycaemic events compared with those not diagnosed with dementia for whom the adjusted hazards ratio (HR) was 2.00 (95% CI,1.63–2.66). Glycaemic control was tighter in patients after dementia diagnosis compared to glycaemic control before dementia diagnosis. The rate of hypoglycaemia six months after dementia diagnosis was significantly higher at 3.05% (95% CI 3.0%–3.1%) compared to the rate of hypoglycaemia before dementia diagnosis at 2.18% (95% CI 2.1%–2.2%). Conclusion: This project highlighted the clinical impact of dementia on patients with DM and confirmed that dementia was associated with an increased risk of hypoglycaemia. Therefore, physicians need to take extra care regarding diabetes management, especially for patients who have been diagnosed with dementia

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe