相关论文: Designing Technologies for Value-based Mental Heal…
Routinely collected clinical patient data posits a valuable resource for data-driven medical innovation. Such secondary data use for medical research purposes is dependent on the patient's consent. To gain an understanding of the patients'…
In the digital health domain, ethical data collection practices are crucial for ensuring the availability of quality datasets that drive medical advancement. Data donation, allowing patients to share their medical data for secondary…
Mental health disorders remain a significant challenge in modern healthcare, with diagnosis and treatment often relying on subjective patient descriptions and past medical history. To address this issue, we propose a personalized mental…
Advances in data collection enable the capture of rich patient-generated data: from passive sensing (e.g., wearables and smartphones) to active self-reports (e.g., cross-sectional surveys and ecological momentary assessments). Although…
With the growing use of new technologies, healthcare is nowadays undergoing significant changes. Information-based medicine has to exploit medical decision-support systems and requires the analysis of various, heterogeneous data, such as…
In pediatrics, patients, caregivers, and clinicians share responsibility for health decisions, but limited collaboration can undermine outcomes. We conducted a qualitative study examining decision-makers perceptions toward collaborative…
Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices…
Mental healthcare has seen numerous benefits from interactive technologies and artificial intelligence. Various interventions have successfully used intelligent technologies to automate the assessment and evaluation of psychological…
Conventional service design methods are valuable for improving healthcare experience, but are limited in scale and information capture. Based on a constructed database of 2,320 stories from patients and carers with multiple long-term…
Assessing care quality and performance is essential to improve healthcare processes and population health management. However, due to bad system design and lack of access to required data, this assessment is often delayed or not done at…
Mental health problems are on the rise globally and strain national health systems worldwide. Mental disorders are closely associated with fear of stigma, structural barriers such as financial burden, and lack of available services and…
In modern dynamic constantly developing society, more and more people suffer from chronic and serious diseases and doctors and patients need special and sophisticated medical and health support. Accordingly, prominent health stakeholders…
We find ourselves on the ever-shifting cusp of an AI revolution -- with potentially metamorphic implications for the future practice of healthcare. For many, such innovations cannot come quickly enough; as healthcare systems worldwide…
The proliferation of consumer health devices such as smart watches, sleep monitors, smart scales, etc, in many countries, has not only led to growing interest in health monitoring, but also to the development of a countless number of…
In this paper, we present novel research methods for collecting and analyzing personal financial data alongside mental health factors, illustrated through a N=1 case study using data from one individual with bipolar disorder. While we have…
Dementia care requires healthcare professionals to balance a patient's medical needs with a deep understanding of their personal needs, preferences, and emotional cues. However, current digital tools prioritise quantitative metrics over…
Objective: Our study objective is to design a feasible technology solution for health organizations to remove barriers to evidence-based clinical information retrieval, and improve Evidence-Based Practice. Methods: Literature from 2010 to…
Clinical decision support tools rooted in machine learning and optimization can provide significant value to healthcare providers, including through better management of intensive care units. In particular, it is important that the patient…
Healthcare professionals (HCPs) face increasing levels of stress and burnout. Technological wellbeing interventions provide accessible and flexible support for HCPs. While most studies have focused on mobile- and web-based programs,…
Healthcare professionals have long envisioned using the enormous processing powers of computers to discover new facts and medical knowledge locked inside electronic health records. These vast medical archives contain time-resolved…