A5089344753- Artificial Intelligence in Healthcare and Education
- Ethics in Clinical Research
- Telemedicine and Telehealth Implementation
- Digital Mental Health Interventions
- Mobile Health and mHealth Applications
- Health Systems, Economic Evaluations, Quality of Life
- Machine Learning in Healthcare
- Ethics and Social Impacts of AI
- Healthcare cost, quality, practices
- COVID-19 and healthcare impacts
- Artificial Intelligence in Healthcare
- Explainable Artificial Intelligence (XAI)
- Literature Analysis and Criticism
- Autopsy Techniques and Outcomes
- Health, Environment, Cognitive Aging
- Climate Change and Health Impacts
- Health Policy Implementation Science
Harvard University
2021-2022
Although advanced analytical techniques falling under the umbrella heading of artificial intelligence (AI) may improve health care, use AI in raises safety and ethical concerns. There are currently no internationally recognized governance mechanisms (policies, standards, evaluation, regulation) for developing using technologies care. A lack international consensus creates technical social barriers to while potentially hampering market competition.The aim this study is review current data...
Healthcare provision has a significant climate impact and, conversely, the is determinant of population health. Research underway to quantify emissions from healthcare systems, which helps with reducing and offsetting them. Artificial intelligence (AI) rapidly developing field contributing English National Health Service (NHS) goals more efficient care reduced impact. There are concerns about detrimental carbon training deploying AI models. Conversely, could potentially reduce through...
Background The COVID-19 pandemic drove investment and research into medical imaging platforms to provide data create artificial intelligence (AI) algorithms for the management of patients with COVID-19. Building on success England’s National Chest Imaging Database, national digital policy body (NHSX) sought a generalized platform development, validation, deployment algorithms. Objective This study aims understand international use cases development implementation inform creation platform....
The potential presented by Artificial Intelligence (AI) for healthcare has long been recognised the technical community.More recently, this policymakers, resulting in considerable public and private investment development of AI across globe.Despite this, excepting limited success stories, real-world implementation systems into frontline limited.There are numerous reasons but a main contributory factor is lack internationally accepted, or formalised, regulatory standards to assess safety...
Digital health interventions (DHIs) have the potential to improve public by combining effective and population reach. However, what biomedical researchers digital developers consider an intervention differs, thereby creating ongoing challenge integrating their respective approaches when evaluating DHIs.This study aims report on Public Health England (PHE) initiative set out operationalize evaluation framework that combines demonstrates impact, cost-effectiveness, benefit of DHIs health.We...
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<sec> <title>UNSTRUCTURED</title> The potential presented by Artificial Intelligence (AI) for healthcare has long been recognised the technical community. More recently, this policymakers, resulting in considerable public and private investment development of AI across globe. Despite this, excepting limited success stories, real-world implementation systems into front-line limited. There are numerous reasons but a main contributory factor is lack internationally accepted, or formalised,...
<sec> <title>BACKGROUND</title> Although advanced analytical techniques falling under the umbrella heading of artificial intelligence (AI) may improve health care, use AI in raises safety and ethical concerns. There are currently no internationally recognized governance mechanisms (policies, standards, evaluation, regulation) for developing using technologies care. A lack international consensus creates technical social barriers to while potentially hampering market competition. </sec>...
The potential presented by Artificial Intelligence (AI) for healthcare has long been recognised the technical community. More recently, this policymakers, resulting in considerable public and private investment development of AI across globe. Despite this, excepting limited success stories, real-world implementation systems into front-line limited. There are numerous reasons but a main contributory factor is lack internationally accepted, or formalised, regulatory standards to assess safety...
<sec> <title>BACKGROUND</title> The COVID-19 pandemic drove investment and research into medical imaging platforms to provide data create artificial intelligence (AI) algorithms for the management of patients with COVID-19. Building on success England’s National Chest Imaging Database, national digital policy body (NHSX) sought a generalized platform development, validation, deployment algorithms. </sec> <title>OBJECTIVE</title> This study aims understand international use cases development...
<sec> <title>BACKGROUND</title> Digital health interventions (DHIs) have the potential to improve public by combining effective and population reach. However, what biomedical researchers digital developers consider an intervention differs, thereby creating ongoing challenge integrating their respective approaches when evaluating DHIs. </sec> <title>OBJECTIVE</title> This study aims report on Public Health England (PHE) initiative set out operationalize evaluation framework that combines...