Workflow Integration Research Articles

Implementing a chest X-ray artificial intelligence tool to enhance tuberculosis screening in India: Lessons learned

Artificial Intelligence (AI) based chest X-ray (CXR) screening for tuberculosis (TB) is becoming increasingly popular. Still, deploying such AI tools can be challenging due to multiple real-life barriers like software installation, workflow integration, network connectivity constraints, limited human resources available to interpret findings, etc. To understand these challenges, PATH implemented a TB REACH active case-finding program in a resource-limited setting of Nagpur in India, where an AI software device (qXR) intended for TB screening using CXR images was used. Eight private CXR laboratories that fulfilled prerequisites for AI software installation were engaged for this program. Key lessons about operational feasibility and accessibility, along with the strategies adopted to overcome these challenges, were learned during this program. This program also helped to screen 10,481 presumptive TB individuals using informal providers based on clinical history. Among them, 2,303 individuals were flagged as presumptive for TB by a radiologist or by AI based on their CXR interpretation. Approximately 15.8% increase in overall TB yield could be attributed to the presence of AI alone because these additional cases were not deemed presumptive for TB by radiologists, but AI was able to identify them. Successful implementation of AI tools like qXR in resource-limited settings in India will require solving real-life implementation challenges for seamless deployment and workflow integration.

A general and modular framework for dark web analysis

The dark web, often linked with illegal activities, can be monitored with different solutions. However, these tools are typically purpose-specific and designed for unique use cases. In this study, we propose a flexible and scalable framework that facilitates the easy integration of new workflows for dark web analysis. The design is based on the control, logic and operations layers, supplemented by a tools module, logs management, asynchronous message-based communication and a database. The implementation maps the features into a microservice approach, utilizing the open-source technologies Docker Swarm, Kafka, ELK Stack (Elastic Search, Logstash and Kibana), and PostgreSQL. A workflow to scrape web elements of Tor onion services is deployed and validated, demonstrating considerable framework performance despite the time-consuming task of navigating the dark web. Over 16 h, the framework collected over half million onion domains (84,371 unique ones) and made 78,555 accesses to them.

Automatic cell-type harmonization and integration across Human Cell Atlas datasets

Harmonizing cell types across the single-cell community and assembling them into a common framework is central to building a standardized Human Cell Atlas. Here, we present CellHint, a predictive clustering tree-based tool to resolve cell-type differences in annotation resolution and technical biases across datasets. CellHint accurately quantifies cell-cell transcriptomic similarities and places cell types into a relationship graph that hierarchically defines shared and unique cell subtypes. Application to multiple immune datasets recapitulates expert-curated annotations. CellHint also reveals underexplored relationships between healthy and diseased lung cell states in eight diseases. Furthermore, we present a workflow for fast cross-dataset integration guided by harmonized cell types and cell hierarchy, which uncovers underappreciated cell types in adult human hippocampus. Finally, we apply CellHint to 12 tissues from 38 datasets, providing a deeply curated cross-tissue database with ∼3.7 million cells and various machine learning models for automatic cell annotation across human tissues.

Applying Implementation Frameworks to Health IT Development in Dementia Care: Lessons from the CareHeroes Project

AbstractBackgroundCaregiving and clinical care for people living with dementia (PLWD) is complex and complicated by communication challenges among caregivers and providers (Gaugler et al., 2022; Ruggiano et al. 2012; 2019). These challenges can constrain decision making about treatment options (Hinton et al., 2007; Miller et al., 2016; Wolff et al., 2020) and may contribute to negative mental health outcomes often reported by family caregivers (Gaugler et al., 2022), which disproportionately impact vulnerable caregivers (e.g., underserved racial/ethnic groups, rural caregivers (Abner et al., 2016; Fabius et al., 2020)). Health information technology (HIT) has been identified as a potential solution to communication challenges in dementia care (Ruggiano et al., 2019; Vedel et al., 2013). However, few studies have reported how to effectively integrate new HIT into practice to support provider‐caregiver communication. In this study, a four‐stage implementation science framework (Meyers et al., 2012) was used to integrate a newly developed web‐based application (app) technology, called CareHeroes (Brown et al., 2016), into clinical practice at two memory clinics to promote caregiver‐physician communication. CareHeroes is multi‐functional and allows secure sharing of patient‐related clinical information between caregivers and providers. It also provides education and support, including an educational chatbot that provides tailored, expert feedback to caregiver questions.MethodEarly stages of implementation involved interviews with caregivers and focus groups with clinic providers to develop a clinical workflow integration plan for the new app. Then, the research team collected user data collected through the app during implementation as well as caregiver psychosocial outcome data (e.g., depression, burden) at baseline and 3‐month follow‐up to evaluate implementation.ResultThirty‐six caregivers and eight clinic providers provided qualitative data that informed the clinical workflow integration plan. The same providers and 21 additional caregivers enrolled in the CareHeroes implementation demonstration study. While user data demonstrated that it was feasible for caregivers to share clinical information and engage in self‐support using CareHeroes, expected outcomes were confounded by complications during the COVID‐19 pandemic.ConclusionThrough using the implementation framework, several lessons were learned regarding potential success and challenges in integrating new HIT into clinical care to support dementia care and caregiving.

Developing the Form and Content of Implementation Strategies to Prevent Venous Thromboembolism for Ambulatory Patients with Cancer

Introduction To prevent venous thromboembolism (VTE) in people with cancer, guidelines recommend risk-assessment for those receiving systemic therapy and anticoagulation (AC) prophylaxis for those at high risk of VTE. However, these recommendations are significantly underused in clinical practice. Our prior work demonstrated barriers and facilitators contributing to this underuse and identified potential implementation strategies to address these barriers. The objective of this study was to develop the form and content of targeted implementation strategies promoting the uptake in clinical practice of guideline-recommendations for VTE prevention for ambulatory patients with cancer. Methods We conducted multidisciplinary stakeholder focus group discussions and semi-structured patient interviews to iteratively design the form and content of five implementation strategies (Table 1): (1) Conduct clinician education and training on risk-assessment models and anticoagulation thromboprophylaxis; (2) Adapt electronic health records (EHR) to provide interactive assistance; (3) Develop and distribute educational materials for clinicians about the Khorana score, VTE risk, and AC counseling; (4) Develop and distribute educational materials for patients; and (5) Audit and feedback. Stakeholders included oncologists, classical hematologists, an oncology clinical pharmacist, oncology advanced practice providers, and oncology patients, in academic and community-based settings within a single health care system. We conducted the clinician focus groups iteratively: in the first session we reviewed guidelines and evidence to support the use of risk assessment and AC prophylaxis in patients with cancer and shared barriers and facilitators identified in our earlier work. During subsequent sessions, we iteratively designed the form and content of the implementation strategies. In the final session, clinicians were presented a finalized prototype of the implementation strategies and asked to perform exploratory usability testing through simulated patient care encounters. Individual semi-structured interviews were conducted with patients to obtain feedback on the design of the implementation strategies and patient-education resources. Results A workflow for integration of risk-assessment and relevant prophylaxis in clinical practice was created based on participant feedback. Details for selected implementation strategies are shown in Table 1. For EHR support, stakeholders recommended the risk-assessment component be integrated within chemotherapy order sets. In addition, they recommended incorporating aid for AC management within the EHR, including a method to assess bleeding risk, pre-populated options for AC thromboprophylaxis, provision of easily accessible links to resources for peri-operative/procedure AC management, and a list of interactions between anticoagulants and common drugs used in oncology practice. Clinician stakeholders also recommended - and subsequently approved - standard phrases available to incorporate into the EHR documentation, both to guide decision-making and to serve as a reminder to re-assess in future visits. For education resources (clinician and patient), clinicians wanted education resources to be concise, and for the patient-facing resource, to be provided to patients both in existing “chemotherapy education” booklets and sent in after-visit appointment instructions. Regarding audit and feedback, clinicians recommended a personalized report card comparing their use of appropriate VTE prevention to their peers. After reviewing the patient-facing education documents, patients recommended simpler, straightforward language and clarifications for the VTE and AC patient education resources based on their past experiences. Conclusions With multidisciplinary stakeholder input from clinicians and patients, we developed a set of implementation strategies designed to address barriers to uptake of VTE prevention recommendations in oncology clinics. Next steps are to test the implementation strategies in clinical practice to measure impact on increasing these evidence-based interventions.

Single-Cell RNA-Seq Analysis of Patient Myeloid-Derived Suppressor Cells and the Response to Inhibition of Bruton's Tyrosine Kinase.

scRNA-seq revealed characteristic gene expression patterns for MDSC from different patients with cancer and BTK inhibition led to the downregulation of multiple genes and pathways important to MDSC function and migration.

Accelerating the design of pili-enabled living materials using an integrative technological workflow.

Bacteria can be programmed to create engineered living materials (ELMs) with self-healing and evolvable functionalities. However, further development of ELMs is greatly hampered by the lack of engineerable nonpathogenic chassis and corresponding programmable endogenous biopolymers. Here, we describe a technological workflow for facilitating ELMs design by rationally integrating bioinformatics, structural biology and synthetic biology technologies. We first develop bioinformatics software, termed Bacteria Biopolymer Sniffer (BBSniffer), that allows fast mining of biopolymers and biopolymer-producing bacteria of interest. As a proof-of-principle study, using existing pathogenic pilus as input, we identify the covalently linked pili (CLP) biosynthetic gene cluster in the industrial workhorse Corynebacterium glutamicum. Genetic manipulation and structural characterization reveal the molecular mechanism of the CLP assembly, ultimately enabling a type of programmable pili for ELM design. Finally, engineering of the CLP-enabled living materials transforms cellulosic biomass into lycopene by coupling the extracellular and intracellular bioconversion ability.

Physicians’ Perceptions of Clinical Decision Support to Treat Patients With Heart Failure in the ED

Clinical decision support (CDS) could help emergency department (ED) physicians treat patients with heart failure (HF) by estimating risk, collating relevant history, and assisting with medication prescribing if physicians' perspectives inform its design and implementation. To evaluate CDS usability and workflow integration in the hands of ED physician end users who use it in clinical practice. This mixed-methods qualitative study administered semistructured interviews to ED physicians from 2 community EDs of Kaiser Permanente Northern California in 2023. The interview guide, based on the Usability Heuristics for User Interface Design and the Sociotechnical Environment models, yielded themes used to construct an electronic survey instrument sent to all ED physicians. Main outcomes were physicians' perceptions of using CDS to complement clinical decision-making, usability, and integration into ED clinical workflow. Seven key informant physicians (5 [71.4%] female, median [IQR] 15.0 [9.5-15.0] years in practice) were interviewed and survey responses from 51 physicians (23 [45.1%] female, median [IQR] 14.0 [9.5-17.0] years in practice) were received from EDs piloting the CDS intervention. Response rate was 67.1% (51 of 76). Physicians suggested changes to CDS accessibility, functionality, and workflow integration. Most agreed that CDS would improve patient care and fewer than half of physicians expressed hesitation about their capacity to consistently comply with its recommendations, citing workload concerns. Physicians preferred a passive prompt that encouraged, but did not mandate, interaction with the CDS. In this qualitative study of physicians who were using a novel CDS intervention to assist with ED management of patients with acute HF, several opportunities were identified to improve usability as well as several key barriers and facilitators to CDS implementation.

BOA: A CT-Based Body and Organ Analysis for Radiologists at the Point of Care.

The study aimed to develop the open-source body and organ analysis (BOA), a comprehensive computed tomography (CT) image segmentation algorithm with a focus on workflow integration. The BOA combines 2 segmentation algorithms: body composition analysis (BCA) and TotalSegmentator. The BCA was trained with the nnU-Net framework using a dataset including 300 CT examinations. The CTs were manually annotated with 11 semantic body regions: subcutaneous tissue, muscle, bone, abdominal cavity, thoracic cavity, glands, mediastinum, pericardium, breast implant, brain, and spinal cord. The models were trained using 5-fold cross-validation, and at inference time, an ensemble was used. Afterward, the segmentation efficiency was evaluated on a separate test set comprising 60 CT scans. In a postprocessing step, a tissue segmentation (muscle, subcutaneous adipose tissue, visceral adipose tissue, intermuscular adipose tissue, epicardial adipose tissue, and paracardial adipose tissue) is created by subclassifying the body regions. The BOA combines this algorithm and the open-source segmentation software TotalSegmentator to have an all-in-one comprehensive selection of segmentations. In addition, it integrates into clinical workflows as a DICOM node-triggered service using the open-source Orthanc research PACS (Picture Archiving and Communication System) server to make the automated segmentation algorithms available to clinicians. The BCA model's performance was evaluated using the Sørensen-Dice score. Finally, the segmentations from the 3 different tools (BCA, TotalSegmentator, and BOA) were compared by assessing the overall percentage of the segmented human body on a separate cohort of 150 whole-body CT scans. The results showed that the BCA outperformed the previous publication, achieving a higher Sørensen-Dice score for the previously existing classes, including subcutaneous tissue (0.971 vs 0.962), muscle (0.959 vs 0.933), abdominal cavity (0.983 vs 0.973), thoracic cavity (0.982 vs 0.965), bone (0.961 vs 0.942), and an overall good segmentation efficiency for newly introduced classes: brain (0.985), breast implant (0.943), glands (0.766), mediastinum (0.880), pericardium (0.964), and spinal cord (0.896). All in all, it achieved a 0.935 average Sørensen-Dice score, which is comparable to the one of the TotalSegmentator (0.94). The TotalSegmentator had a mean voxel body coverage of 31% ± 6%, whereas BCA had a coverage of 75% ± 6% and BOA achieved 93% ± 2%. The open-source BOA merges different segmentation algorithms with a focus on workflow integration through DICOM node integration, offering a comprehensive body segmentation in CT images with a high coverage of the body volume.

Whole genome sequencing in high-grade cervical intraepithelial neoplasia patients from different ethnic groups in China.

Cervical cancer (CC) is the fourth most common cancer in women worldwide. It develops through precancerous lesions (cervical intraepithelial neoplasia (CIN), graded from low-grade (CIN1) to high-grade (CIN2-3)). It is well established that precancerous and cancerous cervical lesions are caused by a persistent infection with high-risk types of the human papilloma virus (hrHPV). To have a deeper understanding of the pathogenesis of CIN and CC, we systematically analyzed the landscape of genomic alterations and HPV integration profiles in high-grade CIN2/3. We performed deep whole genome sequencing on exfoliated cervical cells and matched peripheral blood samples from a cohort of 51 Chinese patients (of whom 35 were HPV+) with high-grade CIN from 3 ethnic groups and constructed strict integrated workflow of genomic analysis. In addition, the HPV types and integration breakpoints in the exfoliated cervical cells from these patients were examined. Genomic analysis identified 6 significantly mutated genes (SMGs), including CDKN2A, PIK3CB, FAM20A, RABEP1, TMPRSS2 and SS18L1, in 51 CIN2/3 samples. As none of them had previously been identified as SMGs in the Cancer Genome Atlas cervical squamous cell carcinoma and endocervical adenocarcinoma (TCGA-CESC) cohort, future studies with larger sample size of CINs may be needed to validate our findings. Mutational signature analysis showed that mutational signatures of CINs were dramatically different from CCs, highlighting their different mutational processes and etiologies. Moreover, non-silent somatic mutations were detected in all of the CIN2/3 samples, and 88% of these mutations occurred in genes that also mutated in CCs of TCGA cohort. CIN2 samples had significantly less non-silent mutations than CIN3 samples (P = .0006). Gene ontology and pathway level analysis revealed that functions of mutated genes were significantly associated with tumorigenesis, thus these genes may be involved in the development and progression of CC. HPV integration breakpoints occurred in 28.6% of the CIN2/3 samples with HPV infection. Integrations of common high risk HPV types in CCs, including HPV16, 52, 58 and 68, also occurred in the CIN samples. Our results lay the groundwork for a deeper understanding of the molecular mechanisms underlying the pathogenesis of CC and pave the way for new tools for screening, diagnosis and treatment of cervical precancerous and cancerous lesions.

Ontology-Based Semantic Construction Image Interpretation

Image-based techniques have become integral to the construction sector, aiding in project planning, progress monitoring, quality control, and documentation. In this paper, we address two key challenges that limit our ability to fully exploit the potential of images. The first is the “semantic gap” between low-level image features and high-level semantic descriptions. The second is the lack of principled integration between images and other digital systems used in construction, such as construction schedules and building information modeling (BIM). These challenges make it difficult to effectively incorporate images into digital twins of construction (DTC), a critical concept that addresses the construction industry’s need for more efficient project management and decision-making. To address these challenges, we first propose an ontology-based construction image interpretation (CII) framework to formalize the interpretation and integration workflow. Then, the DiCon-SII ontology is developed to provide a formalized vocabulary for visual construction contents and features. DiCon-SII also acts as a bridge between images and other digital systems to help construct an image-involved DTC. To evaluate the practical application of DiCon-SII and CII in supporting construction management tasks and as a precursor to DTC, we conducted a case study involving drywall installation. Via this case study, we demonstrate how the proposed methods can be used to infer the operational stage of a construction process, estimate labor productivity, and retrieve specific images based on user queries.

Early Integrated Palliative Care Within a Surgical Oncology Clinic

Advance directive (AD) designation is an important component of advance care planning (ACP) that helps align care with patient goals. However, it is underutilized in high-risk surgical patients with cancer, and multiple barriers contribute to the low AD designation rates in this population. To assess the association of early palliative care integration with changes in AD designation among patients with cancer who underwent surgery. This cohort study was a retrospective analysis of a prospectively maintained registry of adult patients who underwent elective surgery for advanced abdominal and soft tissue malignant tumors at a surgical oncology clinic in a comprehensive cancer center with expertise in regional therapeutics between June 2016 and May 2022, with a median (IQR) postoperative follow-up duration of 27 (15-43) months. Data analysis was conducted from December 2022 to April 2023. Integration of ACP recommendations and early palliative care consultations into the surgical workflow in 2020 using electronic health records (EHR), preoperative checklists, and resident education. The primary outcomes were AD designation and documentation. Multivariable logistic regression was performed to assess factors associated with AD designation and documentation. Among the 326 patients (median [IQR] age 59 [51-67] years; 189 female patients [58.0%]; 243 non-Hispanic White patients [77.9%]) who underwent surgery, 254 patients (77.9%) designated ADs. The designation rate increased from 72.0% (131 of 182 patients) before workflow integration to 85.4% (123 of 144 patients) after workflow integration in 2020 (P = .004). The AD documentation rate did not increase significantly after workflow integration in 2020 (48.9% [89 of 182] ADs documented vs 56.3% [81 of 144] ADs documented; P = .19). AD designation was associated with palliative care consultation (odds ratio [OR], 41.48; 95% CI, 9.59-179.43; P < .001), palliative-intent treatment (OR, 5.12; 95% CI, 1.32-19.89; P = .02), highest age quartile (OR, 3.79; 95% CI, 1.32-10.89; P = .01), and workflow integration (OR, 2.05; 95% CI, 1.01-4.18; P = .048). Patients who self-identified as a race or ethnicity other than non-Hispanic White were less likely to have designated ADs (OR, 0.36; 95% CI, 0.17-0.76; P = .008). AD documentation was associated with palliative care consulation (OR, 4.17; 95% CI, 2.57- 6.77; P < .001) and the highest age quartile (OR, 2.41; 95% CI, 1.21-4.79; P = .01). An integrated ACP initiative was associated with increased AD designation rates among patients with advanced cancer who underwent surgery. These findings demonstrate the feasibility and importance of modifying clinical pathways, integrating EHR-based interventions, and cohabiting palliative care physicians in the surgical workflow for patients with advanced care.

Multi-tissue proteogenomic analysis for mechanistic toxicology studies in non-model species

New approach methodologies (NAM), including omics and in vitro approaches, are contributing to the implementation of 3R (reduction, refinement and replacement) strategies in regulatory science and risk assessment. In this study, we present an integrative transcriptomics and proteomics analysis workflow for the validation and revision of complex fish genomes and demonstrate how proteogenomics expression matrices can be used to support multi-level omics data integration in non-model species in vivo and in vitro. Using Atlantic salmon as an example, we constructed proteogenomic databases from publicly available transcriptomic data and in-house generated RNA-Seq and LC-MS/MS data. Our analysis identified ∼80,000 peptides, providing direct evidence of translation for over 40,000 RefSeq structures. The data also highlighted 183 co-located peptide groups that supported a single transcript each, and in each case, either corrected a previous annotation, supported Ensembl annotations not present in RefSeq, or identified novel previously unannotated genes. Proteogenomics data-derived expression matrices revealed distinct profiles for the different tissue types analyzed. Focusing on proteins involved in defense against xenobiotics, we detected distinct expression patterns across different salmon tissues and observed homology in the expression of chemical defense proteins between in vivo and in vitro liver systems. Our study demonstrates the potential of proteogenomic analyses in extending our understanding of complex fish genomes and provides an advanced bioinformatic toolkit to support the further development of NAMs and their application in regulatory science and (eco)toxicological studies of non-model species.

Patient-Reported Outcome Measures for Patients With CKD: The Case for Patient-Reported Outcomes Measurement Information System (PROMIS) Tools

Chronic kidney disease (CKD), kidney failure, and kidney replacement therapies are associated with high symptom burden and impaired health-related quality of life (HRQOL). Symptoms change with disease progression or transition between treatment modalities and frequently go unreported and unmanaged. Tools that reliably monitor symptoms may improve the management of patients with CKD. Patient-reported outcome measures (PROMs) assess symptom severity; physical, psychological, social, and cognitive functioning; treatment-related side effects; and HRQOL. Systematic use of PROMs can improve patient-provider communication, patient satisfaction, clinical outcomes, and HRQOL. Potential barriers to their use include a lack of engagement, response burden, and limited guidance about PROM collection, score interpretation, and workflow integration. Well-defined, acceptable, and effective clinical response pathways are essential for implementing PROMs. PROMs developed by the Patient-Reported Outcomes Measurement Information System (PROMIS) address some challenges and may be suitable for clinical use among patients with CKD. PROMIS tools assess multiple patient-valued, clinically actionable symptoms and functions. They can be administered as fixed-length, customized short forms or computer adaptive tests, offering precise measurement across a range of symptom severities or function levels, tailored questions to individuals, and reduced question burden. Here we provide an overview of the potential use of PROMs in CKD care, with a focus on PROMIS.

Unveiling the potential of galectin-3 as a diagnostic biomarker for pancreatic cancer: a review

Early detection of pancreatic cancer is crucial for improving patient outcomes, and identifying reliable biomarkers is a critical research area in this field. Galectin-3 (Gal-3) is a promising candidate for utilisation as a diagnostic biomarker in early-stage pancreatic cancer. This review aims to explore the potential of Gal-3 in pancreatic cancer diagnosis and its implications for precision medicine. Rigorous validation studies are essential to establish the clinical utility of Gal-3, including large-scale investigations to assess its sensitivity, specificity, and predictive value. Combining Gal-3 with existing biomarkers and advanced imaging techniques may enhance the accuracy of early detection. Moreover, Gal-3 holds promise for risk stratification, enabling the identification of high-risk individuals who could benefit from intensified surveillance and early interventions. However, challenges in standardised testing protocols, establishing reference ranges, assay reliability, workflow integration, cost-effectiveness, and healthcare provider education must be addressed for successful implementation. Despite these challenges, Gal-3 presents significant implications for precision medicine in pancreatic cancer management. By unravelling its potential and overcoming the hurdles, Gal-3 could revolutionise early detection, risk stratification, and personalised approaches in pancreatic cancer care. Collaborative efforts and continued research will be crucial in harnessing the full potential of Gal-3 as a diagnostic biomarker for early-stage pancreatic cancer.

Parametric Integration of CFD-based Wind Pressure Coefficients into Building Energy Models: A Novel Workflow

By integrating computational fluid dynamics (CFD)-generated wind pressure coefficients (WPCs) into building energy models, recent workflows enable the evaluation of the impacts of local wind on the energy performance of buildings. With the current workflows, however, only manual integration of WPCs into building energy models is possible. This study provides a workflow for the parametric integration of CFD-based WPCs, sampled for each window in the model, into building energy models using the Rhino-GH platform. Using this workflow, this study performed a parametric block-scale energy evaluation of 324 iterations for courtyard and high-rise layouts in various urban and building design configurations in the climate of Tel Aviv to compare the cooling load deviations between CFD-based and default WPCs. The results reveal a significant cooling load deviation between default and CFD-based WPCs, particularly in compact configurations (courtyard typology, higher FAR, and narrower street widths), indicating that default wind pressure coefficients overestimate the natural cooling potential. Further investigation of the balance between solar gains and convective heat losses reveals a surge in the impact of solar gains on cooling loads when accounting for CFD-based WPCs in the climate of Tel Aviv. This workflow can assist designers and analysts in accounting for local wind patterns in energy-driven urban design workflows.

Pemanfaatan Teknologi Informasi dalam Praktik Keperawatan

This study aims to determine the use of information technology in nursing practices. The method used is a systematic review with the preferred reporting items for systematic review and meta-analysis (prism). The search uses the Boolean phrase "information," "Technology," "Nursing Care," and "Nursing Practice". Literature studies consider original articles, sources from journals, and articles in English. They are available as complete text from international databases, e.g., Science Direct, Scopus, Sage, PubMed, and Proquest. To analyze using Joanna Briggs Institute (JBI). The results showed that information technology can help nurses in increasing collaboration and clinical, supporting decisions in facilitating the integration of clinical workflow between nurses and other medical professionals, improving the quality and efficiency of medical and maintenance services, facilitating communication management in the technology environment, increasing information documentation, Management, and monitoring, improving resource management, improving performance and satisfaction management, policy making, and facilitating the path of organizational and professional growth. CONCLUSION: IT can help nurses increase collaboration and clinical decision support in promoting the integration of clinical workflows between nurses and other medical professionals, satisfaction management, policy making, and reducing the path of organizational and professional growth.&#x0D; &#x0D; Keywords: Nursing Care, Information, Nursing Practices, Technology

How Interoperability Challenges Are Addressed in Healthcare IoT Projects.

The rapid development and implementation of Internet of Medical Things has made interoperability a serious challenge. In this scoping review, we provide an overview of the interoperability challenge, as reported in the health literature, and highlight the proposed solutions. After searching between January 2018 and June 2023 in Compendex via Engineering Village and PubMed, we found 18 publications. The interoperability challenges identified were device heterogeneity, system heterogeneity, data standardization, security and safety, system and architecture standard, system and workflow integration and regulatory and compliance requirements. Solutions included ontology approaches, conceptual semantic frameworks, improved standards, design of middleware, and using blockchain technology.

Cheminformatics Microservice: unifying access to open cheminformatics toolkits

In recent years, cheminformatics has experienced significant advancements through the development of new open-source software tools based on various cheminformatics programming toolkits. However, adopting these toolkits presents challenges, including proper installation, setup, deployment, and compatibility management. In this work, we present the Cheminformatics Microservice. This open-source solution provides a unified interface for accessing commonly used functionalities of multiple cheminformatics toolkits, namely RDKit, Chemistry Development Kit (CDK), and Open Babel. In addition, more advanced functionalities like structure generation and Optical Chemical Structure Recognition (OCSR) are made available through the Cheminformatics Microservice based on pre-existing tools. The software service also enables developers to extend the functionalities easily and to seamlessly integrate them with existing workflows and applications. It is built on FastAPI and containerized using Docker, making it highly scalable. An instance of the microservice is publicly available at https://api.naturalproducts.net. The source code is publicly accessible on GitHub, accompanied by comprehensive documentation, version control, and continuous integration and deployment workflows. All resources can be found at the following link: https://github.com/Steinbeck-Lab/cheminformatics-microservice.Graphical

Current knowledge and availability of machine learning across the spectrum of trauma science.

Recent technological advances have accelerated the use of Machine Learning in trauma science. This review provides an overview on the available evidence for research and patient care. The review aims to familiarize clinicians with this rapidly evolving field, offer perspectives, and identify existing and future challenges. The available evidence predominantly focuses on retrospective algorithm construction to predict outcomes. Few studies have explored actionable outcomes, workflow integration, or the impact on patient care. Machine Learning and data science have the potential to simplify data capture and enhance counterfactual causal inference research from observational data to address complex issues. However, regulatory, legal, and ethical challenges associated with the use of Machine Learning in trauma care deserve particular attention. Machine Learning holds promise for actionable decision support in trauma science, but rigorous proof-of-concept studies are urgently needed. Future research should assess workflow integration, human-machine interaction, and, most importantly, the impact on patient outcome. Machine Learning enhanced causal inference for observational data carries an enormous potential to change trauma research as complement to randomized studies. The scientific trauma community needs to engage with the existing challenges to drive progress in the field.