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Next generation brain health: transforming global research and public health to promote prevention of dementia and reduce its risk in young adult populations.
Lancet Healthy Longev
December 2024
Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland; Centre for Dementia Research, School of Health, Leeds Beckett University, Leeds, UK.
Efforts to prevent dementia can benefit from precision interventions delivered to the right population at the right time; that is, when the potential to reduce risk is the highest. Young adults (aged 18-39 years) are a neglected population in dementia research and policy making despite being highly exposed to several known modifiable risk factors. The risk and protective factors that have the biggest effect on dementia outcomes in young adulthood, and how these associations differ across regions and groups, still remain unclear.
View Article and Find Full Text PDFFrom the 100 Day Mission to 100 lines of software development: how to improve early outbreak analytics.
Lancet Digit Health
December 2024
Infectious Disease Epidemiology and Dynamics, London School of Hygiene and Tropical Medicine, London, UK.
Since the COVID-19 pandemic, considerable advances have been made to improve epidemic preparedness by accelerating diagnostics, therapeutics, and vaccine development. However, we argue that it is crucial to make equivalent efforts in the field of outbreak analytics to help ensure reliable, evidence-based decision making. To explore the challenges and key priorities in the field of outbreak analytics, the Epiverse-TRACE initiative brought together a multidisciplinary group of experts, including field epidemiologists, data scientists, academics, and software engineers from public health institutions across multiple countries.
View Article and Find Full Text PDFBenefits and harms associated with the use of AI-related algorithmic decision-making systems by healthcare professionals: a systematic review.
Lancet Reg Health Eur
January 2025
Harding Center for Risk Literacy, Faculty of Health Sciences Brandenburg, University of Potsdam, Virchowstr. 2, Potsdam 14482, Germany.
Background: Despite notable advancements in artificial intelligence (AI) that enable complex systems to perform certain tasks more accurately than medical experts, the impact on patient-relevant outcomes remains uncertain. To address this gap, this systematic review assesses the benefits and harms associated with AI-related algorithmic decision-making (ADM) systems used by healthcare professionals, compared to standard care.
Methods: In accordance with the PRISMA guidelines, we included interventional and observational studies published as peer-reviewed full-text articles that met the following criteria: human patients; interventions involving algorithmic decision-making systems, developed with and/or utilizing machine learning (ML); and outcomes describing patient-relevant benefits and harms that directly affect health and quality of life, such as mortality and morbidity.
Prioritization of Surgical, Obstetric, Trauma, and Anesthesia Care in South and Southeast Asian Countries' Health Planning and Policy‑making: SOTA Care Policies in South and Southeast Asia.
Ann Glob Health
December 2024
Association for Socially Applicable Research (ASAR), Pune, Maharashtra, India.
Lack of policy prioritization of surgical, obstetric, trauma and anesthesia (SOTA) care in South and Southeast Asian countries could be a potential contributor to limited access to care. To assess the SOTA care prioritization in National Health Policies, Strategies, and Plans (NHPSPs). We analyzed NHPSPs from twelve South and Southeast Asian countries.
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