Mapping the regulatory landscape for artificial intelligence in health within the European Union.

Regulatory frameworks for artificial intelligence (AI) are needed to mitigate risks while ensuring the ethical, secure, and effective implementation of AI technology in healthcare and population health. In this article, we present a synthesis of 141 binding policies applicable to AI in healthcare and population health in the EU and 10 European countries. The EU AI Act sets the overall regulatory framework for AI, while other legislations set social, health, and human rights standards, address the safety of technologies and the implementation of innovation, and ensure the protection and safe use of data.

The top 10 priorities in adults living with type 1 diabetes in Ireland and the United Kingdom - A James Lind Alliance priority setting partnership.

Aims: To undertake a Priority Setting Partnership (PSP), identifying the most important unanswered questions in type 1 diabetes in Ireland and the United Kingdom and to compare these to priorities identified in a 2011 PSP.

Methods: A steering committee (including eight individuals with lived experience/charity representatives and six clinicians) designed a survey which asked stakeholders to list three questions about type 1 diabetes. This was disseminated through social media, direct email contact, and printed posters.

Acceptability, Perceptions, and Experiences Regarding Electronic Patient-Reported Outcomes After Laparoscopic Cholecystectomy: Protocol for a Mixed Methods Feasibility Study.

Background: Patient-reported outcomes (PROs) can be defined as any report of a patient's health taken directly from the patient. Routine collection of PRO data has been shown to offer potential benefits to patient-doctor communication. Electronic forms of PRO measures (PROMs) could be more beneficial in comparison to traditional PROMs in obtaining PROs from patients.

Identifying Barriers to the Adoption of Digital Contact Tracing Apps in England: Semistructured Interview Study With Professionals Involved in the Pandemic Response.

Background: The NHS (National Health Service) COVID-19 app was a digital contact tracing app (DCTA) used in England in response to the COVID-19 pandemic. The aim of which was to limit the spread of COVID-19 by providing exposure alerts. At the time of the pandemic, questions were raised regarding the effectiveness and cost of the NHS COVID-19 app and whether DCTAs have a role in future pandemics.

Educational and psychological interventions for managing atopic dermatitis (eczema).

Background: Atopic dermatitis (eczema), can have a significant impact on well-being and quality of life for affected people and their families. Standard treatment is avoidance of triggers or irritants and regular application of emollients and topical steroids or calcineurin inhibitors. Thorough physical and psychological assessment is central to good-quality treatment.

A plain language summary of the results from the phase 2b HERIZON-BTC-01 study of zanidatamab in participants with HER2-amplified biliary tract cancer.

What Is This Summary About?: Researchers wanted to study whether the research drug zanidatamab could help people with a type of cancer called biliary tract cancer. In some people, biliary tract cancer cells make extra copies of a gene called HER2 (also called ERBB2). This is known as being HER2-amplified.

Early warning of trends in commercial wildlife trade through novel machine-learning analysis of patent filing.

Unsustainable wildlife trade imperils thousands of species, but efforts to identify and reduce these threats are hampered by rapidly evolving commercial markets. Businesses trading wildlife-derived products innovate to remain competitive, and the patents they file to protect their innovations also provide an early-warning of market shifts. Here, we develop a novel machine-learning approach to analyse patent-filing trends and apply it to patents filed from 1970-2020 related to six traded taxa that vary in trade legality, threat level, and use type: rhinoceroses, pangolins, bears, sturgeon, horseshoe crabs, and caterpillar fungus.

Identifying the key characteristics, trends, and seasonality of pedestrian traffic injury at a major trauma center in Saudi Arabia: a registry-based retrospective cohort study, 2017-2022.

Background: Pedestrian traffic injuries are a rising public health concern worldwide. In rapidly urbanizing countries like Saudi Arabia, these injuries account for a considerable proportion of trauma cases and represent a challenge for healthcare systems. The study aims to analyze the key characteristics, seasonality, and outcomes of pedestrian traffic injuries in Riyadh, Saudi Arabia.

Health facilities readiness for standard precautions to infection prevention and control in Nepal: A secondary analysis of Nepal Health Facility Survey 2021.

Background: Improvements in standard precaution related to infection prevention and control (IPC) at the national and local-level health facilities (HFs) are critical to ensuring patient's safety, preventing healthcare-associated infections (HAIs), mitigating Antimicrobial Resistance (AMR), protecting health workers, and improving trust in HFs. This study aimed to assess HF's readiness to implement standard precautions for IPC in Nepal.

Methods: This study conducted a secondary analysis of the nationally-representative Nepal Health Facility Survey (NHFS) 2021 data and used the Service Availability and Readiness Assessment (SARA) Manual from the World Health Organization (WHO) to examine the HF's readiness to implement standard precautions for IPC.

Resource Utilization and Costs Associated With Cardiogenic Shock Complicating Myocardial Infarction: A Population-Based Cohort Study.

Background: Cardiogenic shock due to acute myocardial infarction (AMI-CS) is associated with significant short- and long-term morbidity and mortality. Despite this, little is known about associated cost.

Objectives: The purpose of this study was to evaluate the health care costs and resource use associated with AMI-CS using administrative data from the province of Ontario, Canada.

AI Hesitancy and Acceptability-Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study.

Background: Artificial intelligence (AI) chatbots have the potential to assist individuals with chronic health conditions by providing tailored information, monitoring symptoms, and offering mental health support. Despite their potential benefits, research on public attitudes toward health care chatbots is still limited. To effectively support individuals with long-term health conditions like long COVID (or post-COVID-19 condition), it is crucial to understand their perspectives and preferences regarding the use of AI chatbots.

Policy implementation and recommended actions to create healthy food environments using the Healthy Food Environment Policy Index (Food-EPI): a comparative analysis in South Asia.

Background: The increasing prevalence of diet-related non-communicable diseases (NCDs) in South Asia is concerning, with type 2 diabetes projected to rise to 68%, compared to the global increase of 44%. Encouraging healthy diets requires stronger policies for healthier food environments.

Methods: This study reviewed and assessed food environment policies in Bangladesh, India, Pakistan, and Sri Lanka from 2020 to 2022 using the Healthy Food Environment Policy Index (Food-EPI) and compared them with global best practices.

Improvements in data completeness in health information systems reveal racial inequalities: longitudinal national data from hospital admissions in Brazil 2010-2022.

Background: Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals.

PM-bound trace elements in pan-European urban atmosphere.

Although many studies have discussed the impact of Europe's air quality, very limited research focused on the detailed phenomenology of ambient trace elements (TEs) in PM in urban atmosphere. This study compiled long-term (2013-2022) measurements of speciation of ambient urban PM from 55 sites of 7 countries (Switzerland, Spain, France, Greece, Italy, Portugal, UK), aiming to elucidate the phenomenology of 20 TEs in PM in urban Europe. The monitoring sites comprised urban background (UB, n = 26), traffic (TR, n = 10), industrial (IN, n = 5), suburban background (SUB, n = 7), and rural background (RB, n = 7) types.

Optimal Significance Levels and Sample Sizes for Signal Detection Methods Based on Non-constant Hazards.

Background And Objectives: Statistical methods for signal detection of adverse drug reactions (ADRs) in electronic health records (EHRs) need information about optimal significance levels and sample sizes to achieve sufficient power. Sauzet and Cornelius proposed tests for signal detection based on the hazard functions of Weibull type distributions (WSP tests) which use the time-to-event information available in EHRs. Optimal significance levels and sample sizes for the application of the WPS tests are derived.

Patients' Preferences for Cytoreductive Treatments in Newly Diagnosed Metastatic Prostate Cancer: The IP5-MATTER Study.

Background And Objective: Cytoreductive treatments for patients diagnosed with de novo synchronous metastatic hormone-sensitive prostate cancer (mHSPC) confer incremental survival benefits over systemic therapy, but these may lead to added toxicity and morbidity. Our objective was to determine patients' preferences for, and trade-offs between, additional cytoreductive prostate and metastasis-directed interventions.

Methods: A prospective multicentre discrete choice experiment trial was conducted at 30 hospitals in the UK between December 3, 2020 and January 25, 2023 (NCT04590976).

Application of Artificial Intelligence in rehabilitation science: A scientometric investigation Utilizing Citespace.

This study presents a scientometric analysis of the intersection between rehabilitation science and artificial intelligence (AI) technologies, using data from the Web of Science (WOS) database from 2002 to 2022. The analysis employed a comprehensive search query with key AI-related terms, focusing on a wide range of publications in rehabilitation science. Utilizing the Citespace tool, the study visualizes and quantifies the relationships between key terms, identifies research trends, and assesses the impact of AI technologies in rehabilitation science.