Decision support system

This study begins by considering the resource-sharing characteristics of scientific research projects to address the issues of resource misalignment and conflict in scientific research project management. It comprehensively evaluates the tangible and intangible resources required during project execution and establishes a resource conflict risk index system. Subsequently, a resource conflict risk management model for scientific research projects is developed using Back Propagation (BP) neural networks. This model incorporates the Dropout regularization technique to enhance the generalization capacity of the BP neural network...

This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection in LN. This study included 111 non-infected LN patients, 72 infected LN patients, and 206 healthy controls (HCs). Patient information, infection characteristics, medication, and laboratory indexes were recorded. Eight ML methods were compared to establish a model through a training group and verify the results in a test group...

Diet shift is an opportunity to mitigate the impacts of food systems, which are responsible for about a third of greenhouse gas (GHG) emissions globally and exert various environmental pressures on ecosystems. This study evaluates the mitigation potential of both global and local environmental impacts through dietary changes within the Brazilian context. Furthermore, the study aims to identify the potential benefits and trade-offs that may arise from these dietary transitions, thus providing a comprehensive analysis of the overall environmental implications...

Patient reported outcomes (PROs) are measures of patients' health that are conveyed directly by individual patients. These measures serve as instruments to evaluate the impact of interventions on any aspect of patients' health, from specific symptoms to broader quality-of-life indicators. However, their effectiveness relies on capturing relevant factors accurately. While commonly utilized in clinical trials, PROs extend their influence across healthcare settings, informing clinicians, healthcare payers, regulators, and administrators to guide quality improvement and reimbursement decisions...

BACKGROUND: Cardiovascular conditions (eg, cardiac and coronary conditions, hypertensive disorders of pregnancy, and cardiomyopathies) were the leading cause of maternal mortality between 2017 and 2019. The United States has the highest maternal mortality rate of any high-income nation, disproportionately impacting those who identify as non-Hispanic Black or Hispanic. Novel clinical approaches to the detection and diagnosis of cardiovascular conditions are therefore imperative. Emerging research is demonstrating that machine learning (ML) is a promising tool for detecting patients at increased risk for hypertensive disorders during pregnancy...

BACKGROUND: Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists. OBJECTIVE: This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain...

PURPOSE: We studied a pediatric group of patients with sellar-suprasellar tumors, aiming to develop a convolutional deep learning algorithm for radiological assistance to classify them into their respective cohort. METHODS: T1w and T2w preoperative magnetic resonance images of 226 Chilean patients were collected at the Institute of Neurosurgery Dr. Alfonso Asenjo (INCA), which were divided into three classes: healthy control (68 subjects), craniopharyngioma (58 subjects) and differential sellar/suprasellar tumors (100 subjects)...

INTRODUCTION: Screening to promote social-emotional well-being in toddlers has positive effects on long-term health and functioning. Communication about social-emotional well-being can be challenging for primary care clinicians for various reasons including lack of time, training and expertise, resource constraints, and cognitive burden. Therefore, we explored clinicians' perspectives on identifying and communicating with caregivers about social-emotional risk in toddlers. METHOD: In 2021, semistructured interviews were conducted with pediatric clinicians (N = 20) practicing in Federally Qualified Health Centers in a single metropolitan area...

Leading national health organizations have declared pediatric mental health an urgent public health issue. Pediatric primary care is an ideal setting to improve mental health in young children; however, various existing barriers limit the effective identification of social-emotional risk among toddlers. This special section of Families, Systems, & Health includes four articles that identify multilevel barriers and facilitators to population-level early childhood mental health screening, identification, and referral and describe implementation strategies that may be used to improve pediatric mental health...

BACKGROUND: "Lock to Live" (L2L) is a novel web-based decision aid for helping people at risk of suicide reduce access to firearms. Researchers have demonstrated that L2L is feasible to use and acceptable to patients, but little is known about how to implement L2L during web-based mental health care and in-person contact with clinicians. OBJECTIVE: The goal of this project was to support the implementation and evaluation of L2L during routine primary care and mental health specialty web-based and in-person encounters...

OBJECTIVE: We applied a user experience (UX) design approach to clinical decision support (CDS) tool development for the specific use case of pediatric asthma. Our objective was to understand physicians' workflows, decision-making processes, barriers (ie, pain points), and facilitators to increase usability of the tool. MATERIALS AND METHODS: We used a mixed-methods approach with semi-structured interviews and surveys. The coded interviews were synthesized into physician-user journey maps (ie, visualization of a process to accomplish goals) and personas (ie, user types)...

OBJECTIVE: To report epidemiological data regarding injury and illness among the Team USA staff during the Tokyo 2020 Summer Olympic and Paralympic Games and Beijing 2022 Winter Olympic and Paralympic Games. METHODS: A retrospective review of all Team USA staff (total staff, N=1703 (62.5% female); total staff days (SD)=34 489) medical encounters during the Tokyo 2020 Games and Beijing 2022 Games was conducted. Details related to injury and illness were evaluated...

BACKGROUND: The global incidence of acute events in psychiatric patients is intensifying, and models to successfully predict acute events have attracted much attention. OBJECTIVE: To explore the influence factors of acute incident severe mental disorders (SMDs) and the application of Rstudio statistical software, and build and verify a nomogram prediction model. METHODS: SMDs were taken as research objects. The questionnaire survey method was adopted to collect data...

BACKGROUND: The human population in Guyana, located on the South American continent, is vulnerable to zoonotic diseases due to an appreciable reliance on Neotropical wildlife as a food source and for trade. An existing suboptimal health surveillance system may affect the effective monitoring of important zoonotic diseases. To effectively address this deficit, a One Health zoonotic disease prioritization workshop was conducted to identify nationally significant zoonoses. METHODS: Prioritization of zoonotic diseases was conducted for the first time in Guyana & Caribbean region using literature review, prioritization criteria and a risk prioritization tool in combination with a consultative One Health workshop...

Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess mental workload from EEG data that use effective brain connectivity for the purpose of extracting features, a hierarchical feature selection algorithm to select the most significant features, and finally machine learning models. We have used the Simultaneous Task EEG Workload (STEW) dataset, an open-access collection of raw EEG data from 48 subjects...

As we emerge from what may be the largest global public health crises of our lives, our community of epidemic modellers is naturally reflecting. What role can modelling play in supporting decision making during epidemics? How could we more effectively interact with policy makers? How should we design future disease surveillance systems? All crucial questions. But who is going to be addressing them in 10 years' time? With high burnout and poor attrition rates in academia, both magnified in our field by our unprecedented efforts during the pandemic, and with low wages coinciding with inflation at its highest for decades, how do we retain talent? This is a multifaceted challenge, that I argue is underpinned by privilege...

Nature loss threatens businesses, the global economy and financial stability. Understanding and addressing these risks for business will require credible measurement approaches and data. This paper explores how natural capital accounting (NCA) can support business data and information needs related to nature, including disclosures aligned with the Taskforce on Nature-related Financial Disclosures recommendations. As businesses seek to measure, manage and disclose their nature-related risks and opportunities, they will need well-organized, consistent and high-quality information regarding their dependencies and impacts on nature, which few businesses currently collect or track in-house...

Equipment demonstrations (demos) play an important role in the evaluation of new systems. As well as the excitement of exploring emerging technologies, a well-organised demo can help guide procurement decisions and support funding applications. However, it is easy to underestimate the substantial effort required both before and following the demo to maximise its potential impact. Here, we discuss how our approach to demos at the Crick Advanced Light Microscopy Science and Technology Platform (CALM-STP) has evolved over the last few years, emphasising the importance of a documented approach that combines quantitative with qualitative comparisons and engages with your user base in order to build up support for any potential system purchase...

BACKGROUND: An ambitious reform of the early access (EA) process was set up in July 2021 in France, aiming to simplify procedures and accelerate access to innovative drugs. OBJECTIVE: This study analyzes the characteristics of oncology drug approvals through the EA process and its impact on real-life data for oncology patients. METHODS: The number and characteristics of EA demands concerning oncology drugs submitted to the National Health Authority (HAS, Haute Autorité de Santé) were reviewed until 31 December 2022...

BACKGROUND: In May 2020, England moved to an opt-out organ donation system, meaning adults are presumed to be an organ donor unless within an excluded group or have opted-out. This change aims to improve organ donation rates following brain or circulatory death. Healthcare staff in the UK are supportive of organ donation, however, both healthcare staff and the public have raised concerns and ethical issues regarding the change. The #options survey was completed by NHS organisations with the aim of understanding awareness and support of the change...