Data Sources Research Articles

Generations of epigenetic clocks and their links to socioeconomic status in the Health and Retirement Study.

Aim: This is a brief description of links between nine epigenetic clocks related to human aging and socioeconomic and behavioral characteristics as well as health outcomes. Materials& methods: We estimate frequently used and novel clocks from one data source, the Health and Retirement Study. Results: While all of these clocks are thought to reflect "aging," they use different CpG sites and do not strongly relate to each other. First and fourth generation clocks are not as linked to socioeconomic status or health outcomes as second and third generation clocks. Conclusion: Epigenetic clocks reflect exciting new tools and their continued evolution is likely to improve our understanding of how exposures get under the skin to accelerate aging.

A Historical Survey of Key Epidemiological Studies of Ionizing Radiation Exposure.

In this article we review the history of key epidemiological studies of populations exposed to ionizing radiation. We highlight historical and recent findings regarding radiation-associated risks for incidence and mortality of cancer and non-cancer outcomes with emphasis on study design and methods of exposure assessment and dose estimation along with brief consideration of sources of bias for a few of the more important studies. We examine the findings from the epidemiological studies of the Japanese atomic bomb survivors, persons exposed to radiation for diagnostic or therapeutic purposes, those exposed to environmental sources including Chornobyl and other reactor accidents, and occupationally exposed cohorts. We also summarize results of pooled studies. These summaries are necessarily brief, but we provide references to more detailed information. We discuss possible future directions of study, to include assessment of susceptible populations, and possible new populations, data sources, study designs and methods of analysis.

Sex differences in post-COVID ageusia/anosmia in the United States

Post-COVID Conditions (PCC) involve persistent symptoms associated with COVID-19 that continue beyond four weeks of initial infection. Sex has been shown to be related with COVID-19 severity and symptoms. The purpose of this study is to assess the loss of taste (ageusia) or smell (anosmia) among U.S. residents who had PCC and examine its specific association with sex. The data source for this cross-sectional study was 2022 Behavioral Risk Factor Surveillance System (BRFSS), a U.S. national dataset. Participants were included if they had COVID-19, reported experiencing PCC, and identified their primary PCC symptom. Overall, 23,824 participants were included in the study. In multivariable logistic regression analysis, adjusted odds ratio for males compared to females was 1.18 (95 % CI: 1.03–1.35; p=0.0165). Participants who were aged <50 years as compared with those who were aged ≥50 years, non-Hispanic white as compared with non-Hispanic black, had BMI ≤ 25 as compared with BMI ≥ 30, had no reported chronic condition as compared with those who did report a chronic condition, and had ≤high school education as compared with those who had > high school education had higher odds of reporting PCC-related ageusia/anosmia in this multivariable model. Among people with PCC, males had an 18 % higher odds of reporting PCC-related ageusia/anosmia as their primary symptom of PCC compared to females. Findings from our study can help identify patients affected by PCC-related ageusia/anosmia who would benefit from early referral for supportive care, such as counseling or interventions that can alleviate this dysfunction.

A qualitative, multi-centre approach to the current state of digitalisation and automation of surveillance in infection prevention and control in German hospitals

BackgroundHealthcare associated infections (HAI) pose a major threat to healthcare systems resulting in an increased burden of disease. Surveillance plays a key role in rapidly identifying these infections and preventing further transmissions. Alas, in German hospitals, the majority of surveillance efforts have been heavily relying on labour intensive processes like manual chart review. In order to be able to identify further starting points for future digital tools and interventions to aid the surveillance of HAI we aimed to gain an understanding of the current state of digitalisation in the context of the general surveillance organisation in German clinics across all care-levels. The end user perspective of infection prevention and control (IPC) professionals was chosen to identify digital interventions that have the biggest impact on the daily surveillance work routines of IPC professionals. Perceived impediments in the advancement of surveillance digitalisation should be explored.MethodsFollowing the development of an interview guideline, eight IPC professionals from seven German hospitals of different care levels were questioned in semi- structured interviews between December 2022 and January 2023. These included questions about general surveillance organisation, access to digital data sources, software to aid the surveillance process as well as current issues in the surveillance process and implementation of software systems. Subsequently, after full transcription, the interview sections were categorized in code categories (first deductive then inductive coding) and analysed qualitatively.ResultsResults were characterised by high heterogeneity in terms of general surveillance organisation and access to digital data sources. Software configuration of hospital and laboratory information systems (HIS/LIS) as well as patient data management systems (PDMS) varied not only between hospitals of different care levels but also between hospitals of the same care level. Outside research projects, neither fully automatic software nor solutions utilising artificial intelligence have currently been implemented in clinical routine in any of the hospitals.ConclusionsAccess to digital data sources and software is increasingly available to aid surveillance of HAI. Nevertheless, surveillance processes in hospitals analysed in this study still heavily rely on manual processes. In the analysed hospitals, there is an implementation and funding gap of (semi-) automatic surveillance solutions in clinical practice, especially in healthcare facilities of lower care levels.

Special Issue on Informatics Education: Characteristics of U.S. Baccalaureate Health Informatics Programs.

Health informatics (HI) is a growing field of study, yet sparse data is available on the characteristics of undergraduate health informatics programs in the United States (U.S.). The lack of a central location for U.S. HI undergraduate program data has led to a gap in information to support current efforts to promote academic standards in the field and attract potential students. The objective of this study was to perform an environment scan of colleges and universities within the U.S. and Puerto Rico to identify undergraduate programs in HI including majors, minors, and undergraduate level certificates. Potential institutions offering HI programs were identified from the National Center for Education Statistics (NCES), Commission for Accreditation of Health Informatics and Health Information Management Education (CAHIIM), the Association of University Programs in Health Administration (AUPHA), the Healthcare Information and Management Systems Society (HIMSS), and the American Health Information Management Association (AHIMA). Publicly available materials for these institutions were reviewed, and data were captured for identified HI programs including geographic location; college or school in which the program was offered; type of degree (if applicable); program title; total credits to complete the program; delivery format; and source of data. 83 HI programs were identified from 60 institutions and 26 states. The primary finding of this environment scan was that inconsistencies exist among U.S. HI undergraduate programs including variations in offering college/school, title of program, number of credits required, delivery formats, CIP codes, and the type of information published on university/college websites. This environment scan was a first step in exploring the characteristics of undergraduate HI programs within the U.S. Further research is needed on the curricular similarities and differences among the programs, the administrative methods of these interdisciplinary programs, and the information most needed by current and potential undergraduate students.

Controlled Noise: Evidence of epigenetic regulation of Single-Cell expression variability.

Understanding single-cell expression variability (scEV) or gene expression noise among cells of the same type and state is crucial for delineating population-level cellular function. While epigenetic mechanisms are widely implicated in gene expression regulation, a definitive link between chromatin accessibility and scEV remains elusive. Recent advances in single-cell techniques enable the study of single-cell multiomics data that include the simultaneous measurement of scATAC-seq and scRNA-seq within individual cells, presenting an unprecedented opportunity to address this gap. This paper introduces an innovative testing pipeline to investigate the association between chromatin accessibility and scEV. With single-cell multiomics data of scATAC-seq and scRNA-seq, the pipeline hinges on comparing the prediction performance of scATAC-seq data on gene expression levels between highly variable genes (HVGs) and non-highly variable genes (non-HVGs). Applying this pipeline to paired scATAC-seq and scRNA-seq data from human hematopoietic stem and progenitor cells, we observed a significantly superior prediction performance of scATAC-seq data for HVGs compared to non-HVGs. Notably, there was substantial overlap between well-predicted genes and HVGs. The gene pathways enriched from well-predicted genes are highly pertinent to cell type-specific functions. Our findings support the notion that scEV largely stems from cell-to-cell variability in chromatin accessibility, providing compelling evidence for the epigenetic regulation of scEV and offering promising avenues for investigating gene regulation mechanisms at the single-cell level. The source code and data used in this paper can be found at https://github.com/SiweiCui/EpigeneticControlOfSingle-CellExpressionVariability. Supplementary data are available at Bioinformatics online.

New approach to NOMA optimization based on individual discrete input continuous output memoryless channel capacity

In NOMA achieving fairness in data transmission for all users is one of the key challenges. It implies a fair allocation of resources among users according to a given criterion. NOMA systems are based on the discreteness of the data source, since the specific nature of data allows to extract information in overloaded systems. Well-known C.E. Shannon capacity equation does not take into account the discrete nature of NOMA group signals, considering them as Gaussian source of information. Therefore, it does not take into account the characteristics of discrete signals used in NOMA systems, which makes it difficult to solve the optimization problem, especially for types of NOMA that use code division. For this task it is necessary to use DCMC capacity. When optimizing total capacity of DCMC, individual properties of users are not taken into account, as a result of which the allocation of resources with such optimization might not be fair. This paper proposes an approach to optimizing NOMA based on the analysis of an-individual mutual information (capacity). The proposed optimization approach allows analyzing the individual characteristics of each user in order to improve NOMA system performance by optimizing NOMA signals parameters.

Applying natural language processing to patient messages to identify depression concerns in cancer patients.

This study aims to explore and develop tools for early identification of depression concerns among cancer patients by leveraging the novel data source of messages sent through a secure patient portal. We developed classifiers based on logistic regression (LR), support vector machines (SVMs), and 2 Bidirectional Encoder Representations from Transformers (BERT) models (original and Reddit-pretrained) on 6600 patient messages from a cancer center (2009-2022), annotated by a panel of healthcare professionals. Performance was compared using AUROC scores, and model fairness and explainability were examined. We also examined correlations between model predictions and depression diagnosis and treatment. BERT and RedditBERT attained AUROC scores of 0.88 and 0.86, respectively, compared to 0.79 for LR and 0.83 for SVM. BERT showed bigger differences in performance across sex, race, and ethnicity than RedditBERT. Patients who sent messages classified as concerning had a higher chance of receiving a depression diagnosis, a prescription for antidepressants, or a referral to the psycho-oncologist. Explanations from BERT and RedditBERT differed, with no clear preference from annotators. We show the potential of BERT and RedditBERT in identifying depression concerns in messages from cancer patients. Performance disparities across demographic groups highlight the need for careful consideration of potential biases. Further research is needed to address biases, evaluate real-world impacts, and ensure responsible integration into clinical settings. This work represents a significant methodological advancement in the early identification of depression concerns among cancer patients. Our work contributes to a route to reduce clinical burden while enhancing overall patient care, leveraging BERT-based models.

Acute care, secondary prevention, and outcomes after ischaemic and haemorrhagic stroke in men and women: a data-linkage study.

Introduction There is evidence that sex differences exist in stroke presentation, risk factors, severity, treatment, and outcomes. To further understand this, we explored how sex differences influence acute stroke management, secondary prevention prescribing and mortality outcomes in a well-characterised cohort of first-ever stroke patients in Scotland. Methods This is a retrospective, population-based, data-linkage study of stroke admissions to acute care hospitals in Scotland between 1 January 2011 and 31 December 2018. Data sources included the Scottish Stroke Care Audit (SSCA), the Prescribing Information System (PIS), the Scottish Morbidity Record 01 (SMR01), and the National Records of Scotland (NRS) Death Records. Multivariable logistic regression was used to explore the association between patient sex, acute stroke care and secondary prevention prescribing, while Cox proportional hazards models were used to explore the association between patient sex and all-cause mortality up to one year after index event. Results This study included 5901 patients with a first-ever intracerebral haemorrhage (ICH) and 47 087 patients with a first-ever acute ischaemic stroke (AIS). After an ICH, women had significantly lower odds of receiving all components of the stroke care bundle (adjusted odds ratio (aOR), 0.78; 95% confidence interval (CI), 0.69 - 0.87) and were less likely to be prescribed antihypertensives within ninety days after discharge (aOR, 0.78; 95% CI, 0.63 - 0.97) to usual place of residence. There was no sex difference in stroke care bundle achievement for those admitted with AIS, however, women had significantly lower odds of receiving antihypertensives, lipid-lowering drugs or oral anticoagulants (OAC) after discharge. The risk of all-cause mortality was lower in women at one year after both ICH (adjusted hazard ratio (aHR), 0.90; 95% CI, 0.83 - 0.98) and AIS (aHR, 0.91; 95% CI, 0.87 - 0.95) after adjusting for potential confounders. Conclusion The sex differences in stroke treatment and outcomes may be partly explained by the older age of women at the time of stroke, which influences stroke presentation, severity, and prognosis. However, following adjustment, women had reduced risk of all-cause mortality after both ICH and AIS.

Unsupervised heterogeneous domain adaptation for EEG classification

Objective. Domain adaptation has been recognized as a potent solution to the challenge of limited training data for electroencephalography (EEG) classification tasks. Existing studies primarily focus on homogeneous environments, however, the heterogeneous properties of EEG data arising from device diversity cannot be overlooked. This motivates the development of heterogeneous domain adaptation methods that can fully exploit the knowledge from an auxiliary heterogeneous domain for EEG classification. Approach. In this article, we propose a novel model named informative representation fusion (IRF) to tackle the problem of unsupervised heterogeneous domain adaptation in the context of EEG data. In IRF, we consider different perspectives of data, i.e. independent identically distributed (iid) and non-iid, to learn different representations. Specifically, from the non-iid perspective, IRF models high-order correlations among data by hypergraphs and develops hypergraph encoders to obtain data representations of each domain. From the non-iid perspective, by applying multi-layer perceptron networks to the source and target domain data, we achieve another type of representation for both domains. Subsequently, an attention mechanism is used to fuse these two types of representations to yield informative features. To learn transferable representations, the maximum mean discrepancy is utilized to align the distributions of the source and target domains based on the fused features. Main results. Experimental results on several real-world datasets demonstrate the effectiveness of the proposed model. Significance. This article handles an EEG classification situation where the source and target EEG data lie in different spaces, and what’s more, under an unsupervised learning setting. This situation is practical in the real world but barely studied in the literature. The proposed model achieves high classification accuracy, and this study is important for the commercial applications of EEG-based BCIs.

Statistics of Periodicals in the Baltic States: Data Sources and Collections

Publishing is a significant part of the cultural, creative, and economic sectors. Its research, assessment, and forecasting require grounded, reliable, accurate, consistent, and comparable statistical data. Considering the lack of research in periodicals statistics and the relevance of publishing statistics, as well as the fact that in the Baltic countries, publishing statistics data are collected by institutions at the same level, the problem arises whether the national libraries’ applied foundational recommendations and legal documents, as well as data collection methodology, can ensure data validity, reliability, comprehensiveness, and comparability. This article aims to examine and compare the data collection practices of periodical statistics in the Baltic States. The research object includes the legal foundation of publishing statistics in Lithuania, Latvia, and Estonia, as well as the 2022 publishing statistics resources and official statistics data collections. UNESCO recommendations and International Organization for Standardization standards can be considered guidelines for such data collection and accounting. The legal foundation of publishing statistics consists of legal deposit laws, which must ensure the sources of statistical data. Even though publishing statistics data are collected by national libraries and the source of statistical data in all countries is legal deposits, the statistical data collections are not identical. Countries choose which data to collect, what criteria to apply, and in what form to present them. It is important to emphasize that data on the publishing industry are not presented in statistical collections, although their collection guidelines and presentation importance are highlighted in international recommendations and normative documents. Statistical data on electronic periodicals are provided only by Estonia. National libraries in the Baltic States are official statistics compilers, so summarized publishing statistics data are provided to national statistics institutions, opening new technological possibilities for data analysis and integration of new data. The collections of statistical data on newspapers and magazines can only be compared according to a few main criteria, as countries have chosen different statistical data presentation features, the main ones being the varying categorization and periodicity characteristics of newspapers and magazines.

Idiopathic sudden sensorineural hearing loss after COVID-19 vaccination: a systematic review and meta-analysis.

To provide pooled analyses on the association between COVID-19 vaccine and the incidence of idiopathic sudden sensorineural hearing loss (ISSNHL). "Medline" via "PubMed", "EMBASE", and "Google scholar". Data sources were inspected from January 2020 to January 2024 using search terms relevant to vaccines for COVID-19. Included were papers with reported numbers of vaccinated populations and incidence if ISSNHL in those populations. Quality assessment was performed with the Newcastle-Ottawa Quality Assessment Scale Criteria. Three publications encompassing more than 191.8 million patients and at least 283 million vaccine doses were included in the quantitative data synthesis. The pooled reported incidence (95%confidence interval) of ISSNHL among COVID-19 vaccine recipients was 1.2588 per 100,000 (0.1385-3.4836). This incidence is significantly lower than the incidence of 5-27 and 60 per 100,000/year reported in the United States and in the European Union, respectively (P < 0.0001). There is no evidence to indicate that the COVID-19 vaccine is associated with the incidence of ISSNHL.

ImplementationOf Dispute Resolutionin the Field Copyright Upon Signing of the Beijing Treaty

Indonesia became a WIPO member country on December 18 2012 co-signed the Beijing Treaty at the World Intellectual General Assembly forum Property Organization in Geneva Switzerland. Implementation of the Beijing Treaty in Indonesia itself is quite interesting to study because the creative industry is in the form of performances Audiovisual in Indonesia itself is a profession so it is needed protection of copyright in the form of moral and economic rights to works audiovisuals, especially those broadcast or shown through media facilities technology. The legal research method used in this research is research normative juridical which is research conducted or aimed only at written regulations with the nature of descriptive analysis research which is a method that functions to describe or provide an overview of the object under study. The data source used is secondary data with analysis quantitative data. The government is expected to make clear policies regarding protection and classification and definition of AudioVisual Works in Indonesia because with Current technological developments make AudioVisual Works increasingly popular developing so that now a clear policy regarding protection is needed AudioVisual work that is in accordance with technological developments, Background The Beijing Treaty itself is linked to several conventions such as the Rome Convention so that the WPPT should be a basis for the government to create policies in the form of statutory regulations to protect works AudioVisual broadcast via electronic media or digital media and The current problems of creative industry players, especially in the field of work AudioVisual regarding the protection and recognition of AudioVisual's works aired through electronic media regarding this matter, it is hoped that the government will which has ratified the Beijing Treaty to create implementing regulations related to registration or recognition mechanisms and claims to the rights of perpetrators The creative industry is specifically related to performers of AudioVisual Works

Penerapan Pelayanan Prima (Service Excellent) pada Pemeriksaan X-Ray di Bandar Udara Internasional Adi Soemarmo Solo

Excellent service has an important role in a business in the field of aviation companies. The main factor in providing satisfaction for customers is that excellent service can provide satisfaction to customers which will then certainly provide good value to the sustainability of the company. Airports have facilities and infrastructure to support service activities such as implementing excellent service at X-Ray checks. Aviation Security officers must apply good excellent service to generate trust and satisfaction to passengers so that researchers are interested in knowing how the application of excellent service by Aviation Security officers to passengers when checking luggage on X-Ray machines and what should be developed in excellent service to passengers at Adi Soemarmo Solo International Airport. This research uses qualitative methods, namely data collection methods in the form of interviews, observation, and documentation. The data obtained in the form of interviews with Aviation Security officers at Adi Soemarmo Solo International Airport and documents used to carry out daily activities. The results of this study indicate an explanation of the data taken by researchers both in terms of observation, interviews, and documentation that the form of service at the X-Ray inspection is the passenger luggage organizer, X-Ray operator, and manual checking of luggage. The results of researcher observations in the application of excellent service to passengers are only 50% and prioritize flight safety security 50%. Based on data sources from interviews conducted by researchers, that the implementation of excellent service strategies carried out by Aviation Security officers is by Applying Hospitality, Organizing passenger queues, Maximizing personnel, and the 3S + 1C Concept.

Identification of dominant tree species based on Resource-1 02D hyperspectral image data

Fine-grained classification of tree species by using high-spectral image data has garnered considerable attention from scholars. In this study, through field measurements from Maguan County, Wenshan Prefecture, Yunnan Province, China, high-spectral image data from the Chinese Resource-1 02D satellite were used as the data source. Various analyses were conducted on the original image’s spectral curve, the spectral curve after envelope removal, the spectral curve after first-order differential transformation, and the spectral curve after second-order differential transformation. A spectral angle mapping classification method was employed to classify and identify four dominant tree species in Maguan County, and the accuracy of the classification results was validated using a confusion matrix. Results indicate that the highest accuracy in tree species classification was achieved when first-order differential transformation and envelope removal were used for the spectral curve; the overall accuracy exceeded 95%, and the kappa value was approximately 0.95. The classification results for the spectral curve after second-order differential transformation were the lowest, with an overall accuracy of 81.69% and a kappa value of 0.76. This research demonstrates that applying first-order differential transformation or envelope removal in combination with spectral angle mapping classification considerably reduces data processing time and improves tree species classification accuracy.

CREdb: A comprehensive database of Cis-Regulatory Elements and their activity in human cells and tissues

BackgroundCis-regulatory elements (CREs) play a pivotal role in gene expression regulation, allowing cells to serve diverse functions and respond to external stimuli. Understanding CREs is essential for personalized medicine and disease research, as an increasing number of genetic variants associated with phenotypes and diseases overlap with CREs. However, existing databases often focus on subsets of regulatory elements and present each identified instance of element individually, confounding the effort to obtain a comprehensive view. To address this gap, we have created CREdb, a comprehensive database with over 10 million human regulatory elements across 1,058 cell types and 315 tissues harmonized from different data sources. We curated and aligned the cell types and tissues to standard ontologies for efficient data query.ResultsData from 11 sources were curated and mapped to standard ontological terms. 11,223,434 combined elements are present in the final database, and these were merged into 5,666,240 consensus elements representing the combined ranges of the individual elements informed by their overlap. Each consensus element contains curated metadata including the number of elements supporting it and a hash linking to the source databases. The inferred activity of each consensus element in various cell-type and tissue context is also provided. Examples presented here show the potential utility of CREdb in annotating non-coding genetic variants and informing chromatin accessibility profiling analysis.ConclusionsWe developed CREdb, a comprehensive database of CREs, to simplify the analysis of CREs by providing a unified framework for researchers. CREdb compiles consensus ranges for each element by integrating the information from all instances identified across various source databases. This unified database facilitates the functional annotation of non-coding genetic variants and complements chromatin accessibility profiling analysis. CREdb will serve as an important resource in expanding our knowledge of the epigenome and its role in human diseases.

A randomized, embedded, pragmatic, Bayesian clinical trial examining clinical decision support for high flow nasal cannula management in children with bronchiolitis: design and statistical analysis plan

BackgroundHigh flow nasal cannula (HFNC) has been increasingly adopted in the past 2 decades as a mode of respiratory support for children hospitalized with bronchiolitis. The growing use of HFNC despite a paucity of high-quality data regarding the therapy’s efficacy has led to concerns about overutilization. We developed an electronic health record (EHR) embedded, quality improvement (QI) oriented clinical trial to determine whether standardized management of HFNC weaning guided by clinical decision support (CDS) results in a reduction in the duration of HFNC compared to usual care for children with bronchiolitis.MethodsThe design and summary of the statistical analysis plan for the REspiratory SupporT for Efficient and cost-Effective Care (REST EEC; “rest easy”) trial are presented. The investigators hypothesize that CDS-coupled, standardized HFNC weaning will reduce the duration of HFNC, the trial’s primary endpoint, for children with bronchiolitis compared to usual care. Data supporting trial design and eventual analyses are collected from the EHR and other real world data sources using existing informatics infrastructure and QI data sources. The trial workflow, including randomization and deployment of the intervention, is embedded within the EHR of a large children’s hospital using existing vendor features. Trial simulations indicate that by assuming a true hazard ratio effect size of 1.27, equivalent to a 6-h reduction in the median duration of HFNC, and enrolling a maximum of 350 children, there will be a > 0.75 probability of declaring superiority (interim analysis posterior probability of intervention effect > 0.99 or final analysis posterior probability of intervention effect > 0.9) and a > 0.85 probability of declaring superiority or the CDS intervention showing promise (final analysis posterior probability of intervention effect > 0.8). Iterative plan-do-study-act cycles are used to monitor the trial and provide targeted education to the workforce.DiscussionThrough incorporation of the trial into usual care workflows, relying on QI tools and resources to support trial conduct, and relying on Bayesian inference to determine whether the intervention is superior to usual care, REST EEC is a learning health system intervention that blends health system operations with active evidence generation to optimize the use of HFNC and associated patient outcomes.Trial registrationClinicalTrials.gov NCT05909566. Registered on June 18, 2023.

Affordable and real-time antimicrobial resistance prediction from multimodal electronic health records

The spread of antimicrobial resistance (AMR) leads to challenging complications and losses of human lives plus medical resources, with a high expectancy of deterioration in the future if the problem is not controlled. From a machine learning perspective, data-driven models could aid clinicians and microbiologists by anticipating the resistance beforehand. Our study serves as the first attempt to harness deep learning (DL) techniques and the multimodal data available in electronic health records (EHR) for predicting AMR. In this work, we utilize and preprocess the MIMIC-IV database extensively to produce separate structured input sources for time-invariant and time-series data customized to the AMR task. Then, a multimodality fusion approach merges the two modalities with clinical notes to determine resistance based on an antibiotic or a pathogen. To efficiently predict AMR, our approach builds the foundation for deploying multimodal DL techniques in clinical practice, leveraging the existing patient data.

Assessment of PERSIANN Satellite Products over the Tulijá River Basin, Mexico

Precipitation is a fundamental component of the Earth’s hydrological cycle. Therefore, monitoring precipitation is paramount, as accurate information is needed to prevent natural hydrological disasters, such as floods and droughts. However, measuring precipitation using rain gauges is complicated due to their sparse spatial distribution. Satellite precipitation products (SPPs) are an alternative source of rainfall data. This study aimed to evaluate the performance of PERSIANN-CCS and PDIR-Now SPPs over the Tulijá River Basin (Chiapas, Mexico) using scatter plots, categorical statistics, descriptive statistics, and decomposing total bias. Additionally, bias correction was performed using the quantile mapping (QM) method. QM is a technique used to improve the fit of SPPs with respect to rainfall observations through a transfer function, aiming to reduce systematic errors in SPPs. The results indicate that the PDIR-Now product tends to overestimate rainfall to a large extent, thus showing better performance in detecting rain events. Meanwhile, PERSIANN-CCS underestimates precipitation to a lesser extent. The findings of this study demonstrate that correcting the bias of SPPs improves estimations of rainfall records, thereby reducing the percentage bias and root mean square error.

Dental care access for children in the United States.

To evaluate access to dental care for children in the United States. The study population included children in 48 states and the District of Columbia. Using multiple data sources, dental care access was estimated at the community level by matching dental care supply and demand using mathematical modeling accounting for access constraints. Outcome measures included percent-met demand, travel distance, and percentage of underserved and unserved communities. Multiple scenarios to improve Medicaid/CHIP participation of dentists were evaluated. Medicaid-insured and CHIP-insured children exhibited lower access compared to those privately insured. The percent-met demand was lower than 50% for Medicaid-insured children and CHIP-insured children for 42 and 34 states, respectively. Percent-met demand was higher than 50% for private-insured children except for Texas and West Virginia. Increasing Medicaid/CHIP participation of dentists resulted in improving access for public-insured children. At 100% Medicaid/CHIP participation, all states exhibited different degrees of percent-met demand increase for publicly insured children, from 7% to 46%. The percent-met demand across all children ranged in 23.8%-82.9% under 70% participation rate versus 22%-83% under 100% participation rate. No single participation rate improved access for all children uniformly across all states. This study found that dental care access was lower for children with public insurance than those with private access across all states, although states responded differently to changes in Medicaid/CHIP participation. Increasing access for children with public insurance would reduce disparities, but overall children's access to dental care would be better improved by expanding the oral health workforce.