Health Management Research Articles

Hyperspectral indices data fusion-based machine learning enhanced by MRMR algorithm for estimating maize chlorophyll content.

Accurate estimation of chlorophyll is essential for monitoring maize health and growth, for which hyperspectral imaging provides rich data. In this context, this paper presents an innovative method to estimate maize chlorophyll by combining hyperspectral indices and advanced machine learning models. The methodology of this study focuses on the development of machine learning models using proprietary hyperspectral indices to estimate corn chlorophyll content. Six advanced machine learning models were used, including robust linear stepwise regression, support vector machines (SVM), fine Gaussian SVM, Matern 5/2 Gaussian stepwise regression, and three-layer neural network. The MRMR algorithm was integrated into the process to improve feature selection by identifying the most informative spectral bands, thereby reducing data redundancy and improving model performance. The results showed significant differences in the performance of the six machine learning models applied to chlorophyll estimation. Among the models, the Matern 5/2 Gaussian process regression model showed the highest prediction accuracy. The model achieved R2 = 0.71 for the training set, RMSE = 338.46 µg/g and MAE = 264.30 µg/g. In the case of the validation set, the Matern 5/2 Gaussian process regression model further improved its performance, reaching R2 =0.79, RMSE=296.37 µg/g, MAE=237.12 µg/g. These metrics show that Matern's 5/2 Gaussian process regression model combined with the MRMR algorithm to select optimal traits is highly effective in predicting corn chlorophyll content. This research has important implications for precision agriculture, particularly for real-time monitoring and management of crop health. Accurate estimation of chlorophyll allows farmers to take timely and targeted action.

Sex disparities in the prevalence, incidence, and management of diabetes mellitus: an Australian retrospective primary healthcare study involving 668,891 individuals

BackgroundIn Australia, diabetes is the fastest growing chronic condition, with prevalence trebling over the past three decades. Despite reported sex differences in diabetes outcomes, disparities in management and health targets remain unclear. This population-based retrospective study used MedicineInsight primary healthcare data to investigate sex differences in diabetes prevalence, incidence, management, and achievement of health targets.MethodsAdults (aged ≥ 18 years) attending 39 general practices in Western Australia were included. Diabetes incidence and prevalence were estimated by age category. Health targets assessed included body mass index (BMI), blood pressure, blood lipids, and glycated haemoglobin (HbA1c) levels. Medical management of diabetes-associated conditions was also investigated. Time-to-incident diabetes was modelled using a Weibull regression. A multilevel mixed-effects logistic regression model investigated risk-adjusted sex differences in achieving the HbA1c health target (HbA1c ≤ 7.0% (≤ 53 mmol/mol)).ResultsRecords of 668,891 individuals (53.4% women) were analysed. Diabetes prevalence ranged from 1.3% (95% confidence interval (CI) 1.2%-1.3%) in those aged < 50 years to 7.2% (95% CI 7.1%-7.3%) in those aged ≥ 50 years and was overall higher in men. In patients younger than 30 years, incidence was higher in women, with this reversing after the age of 50. Among patients with diabetes, BMI ≥ 35 kg/m2 was more prevalent in women, whereas current and past smoking were more common in men. Women were less likely than men to achieve lipid health targets and less likely to receive prescriptions for lipid, blood pressure, or glucose-lowering agents. Men with incident diabetes were 21% less likely than women to meet the HbA1c target. Similarly, ever recorded retinopathy, nephropathy, neuropathy, hypertension, dyslipidaemia, coronary heart disease, heart failure, peripheral vascular disease and peripheral artery disease were higher in men than women.ConclusionsThis research underscores variations in diabetes epidemiology and management based on sex. Tailoring diabetes management should consider the patient's sex.

The potential benefits of extra screening for glycated haemoglobin, total cholesterol and low-density lipoprotein cholesterol on donor health management and retention.

An extra health screening, including glycated haemoglobin (HbA1c), total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C), was initiated for regular donors aged over 40 in Taiwan in November 2015. This study aimed to determine its benefits on donor health management and retention. A stratified random mail survey was conducted among donors who received HbA1c, TC and LDL-C screening between November 2015 and June 2017 to investigate their awareness of the screening, medical histories and post-screening behaviours. Their subsequent screening results and donation records from 3 years before and after the initial screening were obtained up to December 2021. In total, 2070 donors participated in the mail survey, with participation rates ranging 15.7%-23.2% across study groups. The screening newly detected hyperglycaemia in 1.6% (95% confidence interval [CI]: 1.2%-2.0%) and hyperlipidaemia in 1.0% (95% CI: 0.7%-1.4%) of participants, with 42.7% (95% CI: 40.3%-45.2%) of participants unaware of the screening. Participants with initially abnormal or borderline TC or LDL-C results showed significant decreases in the subsequent screening (all p values<0.05). No difference was found in participants' awareness of the screening. However, those who sought medical consultation or made specific lifestyle changes tended to show greater improvements. Awareness of the screening was associated with increased whole blood donations and donated units. The extra health screening has limited benefits for donor health management without additional interventions, but it may motivate donors to donate more frequently. Raising donors' awareness of the screening is also crucial to maximize its benefits.

Exploring the Impact of Information and Health Literacy on Health Management of Senior Adults with Hypertension

This research examines the relationship between information literacy and health issues in senior adults with age-related conditions such as hypertension. Utilizing Chatman's Theory of Life in the Round and drawing from data sourced from Reddit posts, surveys, and interviews, the study investigates the influence of higher education and literacy levels on the frequency of health-related inquiries among a marginalized group, seniors. It also identifies the digital divide as a notable barrier to accessing health information for specific senior individuals. The study underscores the significance of factors such as physical exercise, stress management, educational attainment, and a well-balanced diet in shaping seniors' management of hypertension. Additionally, it emphasizes the vital role of information and health literacy in empowering seniors to make informed decisions about their well-being and health.Furthermore, the study sheds light on seniors' proactive approach to seeking health information and recommends targeted interventions to ensure comprehensive access to health information for all seniors. These interventions are crucial in addressing the unique challenges this demographic faces. The findings from this dissertation provide valuable insights that could aid in designing valuable and practical guidelines and best practices for supporting the management of hypertension in seniors, contributing significantly to understanding how information literacy and health literacy can be harnessed to help seniors effectively manage their health.

Nursing process performance measurement tool based on bloom’s revised taxonomy: A validity and reliability analysis

AimThis study aimed to develop a measurement tool that could evaluate educational approaches by integrating the cognitive dimensions required at each stage of the nursing process and strengthening the connection between education and clinical practice. BackgroundThe nursing process is a core component of nursing practice and supports nurses and nursing students in systematically performing the problem-solving process necessary for patient health management. DesignCross-sectional, methodological study. MethodsA nursing process performance measurement tool that could measure the cognitive dimensions required at each stage of the nursing process was developed based on Anderson’s and Bloom’s revised taxonomy. The data for this study were collected from July to August 2023 at four universities in South Korea. The reliability and validity of the measurement tool were evaluated through a survey conducted on 406 nursing students. Participants were third- and fourth-year nursing students with clinical practice experience, recruited through purposive sampling. ResultsThe developed tool was designed to systematically measure and evaluate each step of the nursing process. This tool consisted of 28 questions, each of which was divided into five assessment questions, six diagnosis questions, six planning questions, five implementation questions and six evaluation questions. Items were rated on a 5-point Likert scale, ranging from 1 (“not at all”) to 5 (“very much”). The measurement score ranged from 28 to 140 points, with higher scores indicating better nursing process performance. The cumulative variance contribution rate of the tool was 68.1 % and the Cronbach’s α value was 0.85 for all items. ConclusionsThis study provides a basis for evaluating educational approaches in nursing curricula by integrating the cognitive dimensions required at each stage of the nursing process. This approach can strengthen the connection between education and clinical practice and can be used not only as a tool to systematically evaluate the learning outcomes of nursing students but also as a standardized nursing process guide.

Health Management of Remote Workers Using Tele-Exercise During The COVID-19 Pandemic in Japan

Health management is increasingly recognized as a vital business resource aimed at enhancing employee well-being. The COVID-19 pandemic has significantly influenced lifestyle habits, underscoring the need for effective health management strategies tailored to thechanging work environment. This study aims to explore the impact of tele-exercise interventions on remote workers group (G1). Itcompares the effects of tele-exercise with those of traditional face-to-face exercise group (G2). Over three months, G1 engaged in a 30-minute weekly exercise program tailored for remote execution, while G2 participated in traditional, in-person sessions. The analysis includedANOVA to assess the differences over time between G1 and G2, Correlation Analysis to examine the relationships among the measuredvariables within each group, and Correspondence Analysis to explore the association patterns between the groups' responses and thevariables of interest. The ANOVA revealed a significant difference in Daily Stress (DS) levels between G1 and G2, with G1 showing higherDS levels. Correlation analysis indicated a strong negative relationship between Body Mass Index (BMI) and Sleep Quality (SQ) in G1, and astrong positive relationship between DS and Satisfaction of Life (SL). Correspondence Analysis showed that that G1 was encompassed in ajob and life satisfaction area, and G2 was encompassed in a sleep and stress for weight control area. This study concluded that both groupsinitially experienced weight gains and increased sleep duration due to remote work. Daily Stress was found to be significantly higher in G1than in G2, possibly due to the isolation of tele-exercise. Correlation analyses highlighted the influence of time on relationship between BMIand SQ, and DS and SL. The study emphasizes stress management and good sleep quality in remote work, with exercise interventionspromoting well-being and productivity.

Workplace mental health promotion in a large state organization: Perceived needs, expected effects, neglected side effects

Background Work ability and mental health in the workplace is increasingly promoted in terms of workplace health management. In order to select suitable interventions at work in a concrete context, employees and managers of a large state organization (science and development sector) were asked about perceived needs, desired effects and possible side effects of health promotion interventions. Methods 13 semi-structured interviews with managers and three focus group interviews with employees (N = 20) were conducted in autumn 2020 by a behavior therapist in training. The evaluation was carried out by a qualitative content analysis of the interview transcripts according to a deductive procedure and was checked by two independent raters. Results Most frequently, need was expressed for individual case counselling by a health expert due to the diversity of work-related problems. Managers would like to see more health-related leadership training, and a review of the various communication channels of their organization. Expected positive effects are increased self-efficacy, higher person-job-fits and reduced absenteeism. Side effects were mentioned, such as confusion of health management activities with therapy, or sensitization effects when speaking too much about mental health in mentally healthy teams. Lack of competence with the topic of mental health was mentioned as a reason for non-participation in mental health promotion activities. Conclusions The role of managers in relation to mental health needs to be more defined. Side effects related to mental health activities should be considered in evaluations. Selection of health interventions should depend on the concrete needs of the organization.

Technology and Continuous Glucose Monitoring Access, Literacy, and Use Among Patients at the Diabetes Center of an Inner-City Safety-Net Hospital: Mixed Methods Study.

Despite the existence of an increasing array of digital technologies and tools for diabetes management, there are disparities in access to and uptake and use of continuous glucose monitoring (CGM) devices, particularly for those most at risk of poor diabetes outcomes. This study aims to assess communication technology and CGM access, literacy, and use among patients receiving treatment for diabetes at an inner-city safety-net hospital. A survey on digital technology ownership and use was self-administered by 75 adults with type 1 and type 2 diabetes at the diabetes clinic of Grady Memorial Hospital in Atlanta, Georgia. In-depth interviews were conducted with 16% (12/75) of these patient participants and 6 health care providers (HCPs) to obtain additional insights into the use of communication technology and CGM to support diabetes self-management. Most participants were African American (66/75, 88%), over half (39/75, 52%) were unemployed or working part time, and 29% (22/75) had no health insurance coverage, while 61% (46/75) had federal coverage. Smartphone ownership and use were near universal; texting and email use were common (63/75, 84% in both cases). Ownership and use of tablets and computers and use and daily use of various forms of media were more prevalent among younger participants and those with type 1 diabetes, who also rated them as easier to use. Technology use specifically for diabetes and health management was low. Participants were supportive of a potential smartphone app for diabetes management, with a high interest in such an app helping them track blood sugar levels and communicate with their care teams. Younger participants showed higher levels of interest, perceived value, and self-efficacy for using an app with these capabilities. History of CGM use was reported by 56% (42/75) of the participants, although half (20/42, 48%) had discontinued use, above all due to the cost of the device and issues with its adhesive. Nonuse was primarily due to not being offered CGM by their HCP. Reasons given for continued use included convenience, improved blood glucose control, and better tracking of blood glucose. The in-depth interviews (n=18) revealed high levels of satisfaction with CGM by users and supported the survey findings regarding reasons for continued use. They also highlighted the value of CGM data to enhance communication between patients and HCPs. Smartphone ownership was near universal among patients receiving care at an inner-city hospital. Alongside the need to address barriers to CGM access and continued use, there is an opportunity to leverage increased access to communication technology in combination with CGM to improve diabetes outcomes among underresourced populations.

Logistic management in public health - A comprehensive review

Logistic management in public health - A comprehensive review

Finding a way in and making it stick: an exploration of chiropractor experiences working in team-oriented elite sport practice settings

Interprofessional healthcare teams have become the benchmark for optimising athlete health and performance in high-stakes sports. Despite a history of utility as provider partners, chiropractors are currently a relatively underutilised...

Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022

A high-accuracy, continuous air temperature (Ta) dataset with high spatiotemporal resolution is essential for human health, disease prediction, and energy management. Existing datasets consider factors such as elevation, latitude, and surface temperature but insufficiently address meteorological and spatiotemporal factors, affecting accuracy. Additionally, no high-resolution dataset currently includes daily maximum (Tmax), minimum (Tmin), and mean (Tmean) temperatures generated using a unified methodology. Here, we introduce the four-dimensional spatiotemporal deep forest (4D-STDF) model, integrating 12 multisource factors, encompassing static and dynamic parameters, and six refined spatiotemporal factors to produce Ta datasets. This approach generates three high-accuracy Ta datasets at 1 km spatial resolution covering mainland China from 2003 to 2022. These datasets, in GeoTIFF format with WGS84 projection, comprise daily Tmax, Tmin, and Tmean. The overall RMSE are 1.49 °C, 1.53 °C, and 1.18 °C for the estimates. The 4D-STDF model can also be applied to other regions with sparse meteorological stations.

Experiences of Indonesian nurses as Hajj health personnel in caring for Hajj pilgrims: A qualitative study.

Investigating the experiences and roles of nurses during Hajj is vital due to the unique public health challenges posed by the mass gathering of diverse pilgrims. Nurses play a crucial role in disease surveillance, infection control, and managing emergencies like heat stroke and injuries. Their insights can improve emergency preparedness and public health management. This study aimed to explore the experiences of Indonesian nurses as Hajj health personnel caring for Hajj pilgrims during the 2023 Hajj season. This study employed a qualitative descriptive design and selected participants through purposive sampling from hospitals, public healthcare centers, and clinics in Yogyakarta, Indonesia. Nine nurses participated in the research, and data were collected through a focus group discussion in December 2023. Thematic analysis was used to analyze the data. Six themes emerged, including practicing ethical principles in providing health care during the hajj process, competency qualifications as a health worker, the health care process during Hajj, legal Requirements for Hajj, the importance of therapeutic communication skills to establish cooperation with various parties, and recognizing the role of duties and responsibilities during the hajj process. The study emphasizes the importance of competencies, ethics, communication, and strategic planning in Hajj healthcare. Effective online communication, especially via WhatsApp, was crucial for coordination. The findings emphasize the need for strategic workforce planning, resource allocation, and continuous training to enhance care quality for pilgrims, informing better planning and policy development for future Hajj seasons.

Decision making techniques in mass gathering medicine during the COVID-19 pandemia: a scoping review.

The COVID-19 pandemic has profoundly affected mass gatherings (MGs) worldwide, necessitating the implementation of advanced decision support techniques. These techniques, including mathematical models and risk assessment tools, have played a critical role in ensuring the safe conduct of events by mitigating the spread of SARS-CoV-2. This mini-review aims to explore and synthesize the decision support methodologies employed in managing MGs during the COVID-19 pandemic. A scoping review was conducted following the PRISMA guidelines covering the period from 2020 to 2024. Studies were categorized by event type (e.g., academic, religious, political, sports) and decision-making tools applied. The review identified a range of decision support techniques, with risk assessment and simulation tools being the most commonly employed across various event types. A total of 199 studies were initially identified, with 10 selected finally for inclusion based on relevance to decision support techniques. Case studies included the successful risk mitigation strategies during the 2020 Hajj, the 2021 Tokyo Olympics, and the 2022 FIFA World Cup in Qatar. Techniques such as fuzzy logic, Bayesian analysis, and multi-criteria decision-making were also highlighted, particularly in complex scenarios. These tools significantly contributed to reducing COVID-19 transmission risks at large-scale events. The review underscores the importance of decision support systems in the safe management of MGs during the pandemic. Further research should focus on the integration of emerging technologies and the long-term impacts of decision support tools on public health management.

Harnessing Nitrogen Use Efficiency for Enhancing Productivity in Rice: A Review

Nitrogen fertilizers have significantly enhanced rice yields over the past decades, but they also have substantial negative impacts on the environment. Excessive application of nutrients, particularly nitrogen, beyond crop requirements is linked to environmental losses. High nitrogen fertilizer input leads to low nitrogen use efficiency (NUE) due to the rapid loss of nitrogen through ammonia volatilization, denitrification, surface runoff, and leaching in the soil-flood water system. Enhancing the yield potential of rice- based cropping systems in response to the global call for carbon neutrality is a crucial research target. New approaches are needed to boost yields while maintaining or ideally reducing nitrogen application to maximize crop NUE. Improving NUE is crucial for addressing the intertwined challenges of environmental degradation, climate change, and food security. This review provides an in-depth exploration of strategies for improving nitrogen use efficiency, including soil health management, optimized fertilizer application, crop management practices, physiological and morphological approaches, exploiting symbiotic relationships, and genetic approaches, all aimed at enhancing rice productivity while addressing agricultural and environmental challenges caused by nitrogen losses, such as ammonia volatilization and leaching and promoting more sustainable farming practices. It also reduces the input costs, leading to a more sustainable agricultural economy and improved living standards for farming communities.

Former jean sandblasters die younger.

Silicosis remains a critical public and occupational health issue, exacerbated by its expansion into non-traditional industries and resulting in significant global morbidity and mortality. This study aims to investigate the death rates associated with silicosis from jean sandblasting by comparing the results of diagnosed individuals to those of the general population. Conducted from 2008 to 2023 in Taşlıçay and Toklular villages, Bingöl City, Turkey, this retrospective cohort study analysed mortality among 220 diagnosed males versus 2851 undiagnosed residents. Data were derived from the Cohort database and validated with the Bingöl Provincial Health Directorate and the Turkish Statistical Institute. Statistical analysis involved univariate comparisons and survival analysis, utilizing the Mann-Whitney U-test, Kruskal-Wallis test and Cox proportional hazards model, with significance set at P < 0.05. The analysis revealed a silicosis mortality rate of 10% in diagnosed individuals over 15 years, notably higher than the 4% in the general population. Higher radiological profusions and younger ages at diagnosis were significant mortality factors. A radiological profusion above five notably increased the mortality risk by 1.37 times, with age and radiological density proving critical in survival rates. This research highlights the increased mortality risk in silicosis patients, particularly among former jean sandblasters, underscoring the significant effects of radiological density and early age exposure on mortality, thereby addressing a crucial gap in understanding the impact of silicosis on life expectancy and community health.

Research progress on community health management model for older adults with chronic diseases and multiple morbidities.

With the rapid ageing of the population, the number of older adults with two or more chronic diseases is increasing. There are individual differences in health assessment, diagnosis, treatment, health management, and medication safety for older adults with chronic conditions and multiple morbidities. Managing these conditions poses increasingly complex challenges for the healthcare system. Developing effective community health management models specifically designed for older adults with multiple chronic diseases is crucial for improving their overall health. This study provides a comprehensive review of the progress in research on community health management models for older adults with multiple chronic diseases, aiming to offer valuable insights for health management in this population.

A method for predicting remaining useful life using enhanced Savitzky–Golay filter and improved deep learning framework

Ensuring operational integrity in large-scale equipment hinges on effective fault prediction and health management. Prognostics and health management (PHM) face the challenge of accurately predicting remaining useful life (RUL) using multivariate sensor data. Traditional methods often require extensive prior knowledge for indicator construction and processing. Deep learning offers a promising alternative. This study presents a multi-channel multi-scale deep learning approach. Initially, an improved Savitzky‒Golay filter (ISG) addresses challenges posed by large and rapidly changing data volumes, enhancing data preprocessing. Subsequently, a framework integrates convolutional neural networks (CNNs) with long short-term memory (LSTM) to capture hierarchical signal information and make integrated predictions. The CNN extracts spatial features from multi-channel input data, while the LSTM captures temporal dependencies. By fusing outputs from both components, the framework enhances predictive accuracy and robustness for complex operational datasets. Experimental validation on the C-MAPSS dataset tests various fusion methods and CNN depths, determining parameters and evaluating filtering effectiveness. Comparative analyses show promising performance, particularly under dynamic conditions. While not optimal for predicting multiple fault types, it outperforms classical algorithms, especially in single fault type prediction tasks.

Protocol for Alberta Societal Health Integration Program (ABSHIP): Community-based Acupuncture Services Model for Social Recovery and Improve Economic Participation

ABSHIP is a first-of-its-kind study that provided integrated acupuncture interventions to enhance pain management while protecting and fostering psychosocial well-being and resilience in children, adolescents, and seniors. The evidence generated from this project will shed light on the utility and cost-effectiveness of integrative care in pain and mental health management

Necessity for a global patient co-owned cloud (GPOC)

BackgroundThe use of Cloud-based storage of personal health records has increased globally. The GPOC Series introduces the concept of a Global Patient co-Owned Cloud (GPOC) of personal health records. Here, we present the GPOC Series’ international survey on the necessity of a GPOC.MethodsOnline global survey with invitations sent to health ministries and major organisations. It received answers from health ministries and affiliated advisors of all 193 United Nations (UN) member states, 2 UN observer states (Holy See & Palestine) and 1 de facto UN non-member state (Taiwan) and from 18 major international organisations. The survey examined a dozen aspects encompassing demographics, privacy, sharing, movability, co-ownership, research, company usage, regulation and the necessity of a GPOC.ResultsThe GPOC Survey elicited responses from 267 individuals from 214 entities, including all UN member states, and major international organisations. Twelve domains were identified, covering demographics, correctness, privacy, commercial use, medical and non-medical research, co-ownership, data sharing, record movement, ownership centralisation, patient rights, environmental concerns, and foundation creation. Results show high agreement on most issues, including support for co-ownership (89%) and movement of personal health records (84%). Disagreement was prominent regarding centralised ownership by the state (64%) and data sharing without consent (85%). Additionally, respondents expressed interest in a neutral, decentralised foundation for regulation (73%) and the environmental sustainability of electronic health records (84%).ConclusionsA Global Patient co-Owned Cloud (GPOC) of personal health records could significantly enhance patient independence and involvement in health management, supported by the near consensus agreement across various domains identified in our survey. This consensus underscores the potential of GPOC to democratise healthcare and align with UN Sustainable Development Goals (SDGs). The survey results demonstrate strong support for GPOC’s role in promoting evidence-based patient management, reducing information silos, and fostering ethical data sharing. Moreover, the overwhelming agreement on key principles of co-ownership, data sharing, and environmental sustainability highlights the global inclination for a decentralised, patient-controlled PHR platform. This platform stands to empower patients worldwide, advance precision medicine, and contribute to the global development and dissemination of artificial intelligence in healthcare.

Exploring omics signature in the cardiovascular response to semaglutide: Mechanistic insights and clinical implications.

Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is a widely used drug for the treatment of type 2 diabetes that offers significant cardiovascular benefits. This review systematically examines the proteomic and metabolomic indicators associated with the cardiovascular effects of semaglutide. A comprehensive literature search was conducted to identify relevant studies. The review utilizes advanced analytical technologies such as mass spectrometry and nuclear magnetic resonance (NMR) to investigate the molecular mechanisms underlying the effects of semaglutide on insulin secretion, weight control, anti-inflammatory activities and lipid metabolism. These "omics" approaches offer critical insights into metabolic changes associated with cardiovascular health. However, challenges remain such as individual variability in expression, the need for comprehensive validation and the integration of these data with clinical parameters. These issues need to be addressed through further research to refine these indicators and increase their clinical utility. Future integration of proteomic and metabolomic data with artificial intelligence (AI) promises to improve prediction and monitoring of cardiovascular outcomes and may enable more accurate and effective management of cardiovascular health in patients with type 2 diabetes. This review highlights the transformative potential of integrating proteomics, metabolomics and AI to advance cardiovascular medicine and improve patient outcomes.