Use of implementation mapping to develop a multifaceted implementation strategy for an electronic prospective surveillance model for cancer rehabilitation.

BACKGROUND: Electronic Prospective Surveillance Models (ePSMs) remotely monitor the rehabilitation needs of people with cancer via patient-reported outcomes at pre-defined time points during cancer care and deliver support, including links to self-management education and community programs, and recommendations for further clinical screening and rehabilitation referrals. Previous guidance on implementing ePSMs lacks sufficient detail on approaches to select implementation strategies for these systems. The purpose of this article is to describe how we developed an implementation plan for REACH, an ePSM system designed for breast, colorectal, lymphoma, and head and neck cancers. METHODS: Implementation Mapping guided the process of developing the implementation plan. We integrated findings from a scoping review and qualitative study our team conducted to identify determinants to implementation, implementation actors and actions, and relevant outcomes. Determinants were categorized using the Consolidated Framework for Implementation Research (CFIR), and the implementation outcomes taxonomy guided the identification of outcomes. Next, determinants were mapped to the Expert Recommendations for Implementing Change (ERIC) taxonomy of strategies using the CFIR-ERIC Matching Tool. The list of strategies produced was refined through discussion amongst our team and feedback from knowledge users considering each strategy's feasibility and importance rating via the Go-Zone plot, feasibility and applicability to the clinical contexts, and use among other ePSMs reported in our scoping review. RESULTS: Of the 39 CFIR constructs, 22 were identified as relevant determinants. Clinic managers, information technology teams, and healthcare providers with key roles in patient education were identified as important actors. The CFIR-ERIC Matching Tool resulted in 50 strategies with Level 1 endorsement and 13 strategies with Level 2 endorsement. The final list of strategies included 1) purposefully re-examine the implementation, 2) tailor strategies, 3) change record systems, 4) conduct educational meetings, 5) distribute educational materials, 6) intervene with patients to enhance uptake and adherence, 7) centralize technical assistance, and 8) use advisory boards and workgroups. CONCLUSION: We present a generalizable method that incorporates steps from Implementation Mapping, engages various knowledge users, and leverages implementation science frameworks to facilitate the development of an implementation strategy. An evaluation of implementation success using the implementation outcomes framework is underway.

Evaluating models of expert judgment to inform assessment of ecosystem viability and collapse.

Expert judgment underpins assessment of threatened ecosystems. However, experts are often narrowly defined, and variability in their judgments may be substantial. Models built from structured elicitation with large diverse expert panels can contribute to more consistent and transparent decision-making. We conducted a structured elicitation under a broad definition of expertise to examine variation in judgments of ecosystem viability and collapse in a critically endangered ecosystem. We explored whether variation in judgments among 83 experts was related to affiliation and management expertise and assessed performance of an average model based on common ecosystem indicators. There were systematic differences among individuals, much of which were not explained by affiliation or expertise. However, of the individuals affiliated with government, those in conservation and environmental departments were more likely to determine a patch was viable than those in agriculture and rural land management. Classification errors from an average model, in which all individuals were weighted equally, were highest among government agriculture experts (27%) and lowest among government conservation experts (12%). Differences were mostly cases in which the average model predicted a patch was viable but the individual thought it was not. These differences arose primarily for areas that were grazed or cleared of mature trees. These areas are often the target of restoration, but they are also valuable for agriculture. These results highlight the potential for conflicting advice and disagreement about policies and actions for conserving and restoring threatened ecosystems. Although adoption of an average model can improve consistency of ecosystem assessment, it can fail to capture and convey diverse opinions held by experts. Structured elicitation and models of ecosystem viability play an important role in providing data-driven evidence of where differences arise among experts to support engagement and discussion among stakeholders and decision makers and to improve the management of threatened ecosystems.

Análisis de los modelos de opiniones de expertos para informar la evaluación de la viabilidad y el colapso ambiental Resumen La evaluación de los ecosistemas amenazados se basa en la opinión de los expertos. Sin embargo, la definición de experto suele ser limitada y la variabilidad de sus juicios puede ser considerable. Los modelos elaborados a partir de consultas estructuradas con grupos de expertos amplios y diversos pueden contribuir a una toma de decisiones más coherente y transparente. Realizamos una consulta estructurada con una definición amplia de experto para analizar la variación en los juicios sobre la viabilidad y el colapso de un ecosistema en peligro crítico. Exploramos si la variación en los juicios entre 83 expertos estaba relacionada con la afiliación y la experiencia en gestión y evaluamos el rendimiento de un modelo medio basado en indicadores comunes del ecosistema. Observamos diferencias sistemáticas entre los expertos, gran parte de las cuales no se explicaban por la afiliación o la experiencia. Sin embargo, entre los expertos vinculados a la administración pública, los de los departamentos de conservación y medio ambiente tenían más probabilidades de determinar que una parcela era viable que los de agricultura y gestión de tierras rurales. Los errores de clasificación de un modelo medio con todos los individuos ponderados por igual, fueron mayores entre los expertos gubernamentales en agricultura (27%) y menores entre los expertos gubernamentales en conservación (12%). En la mayoría de los casos, las diferencias se debían a que el modelo medio predecía que una parcela era viable, pero el individuo pensaba que no lo era. Estas diferencias surgieron sobre todo en zonas que habían sido pastoreadas o con una tala total de árboles maduros. Estas zonas suelen ser objeto de restauración, pero también son valiosas para la agricultura. Estos resultados ponen de manifiesto la posibilidad de que se produzcan consejos contradictorios y desacuerdos sobre las políticas y acciones de conservación y restauración de los ecosistemas pastoreados y forestales. Si bien la adopción de un modelo medio puede mejorar la coherencia de la evaluación de los ecosistemas, también puede fallar a la hora de captar y transmitir las diversas opiniones de los expertos. Las consultas estructuradas y los modelos de viabilidad de los ecosistemas desempeñan un papel importante a la hora de aportar pruebas basadas en datos de dónde surgen las diferencias entre los expertos para apoyar el compromiso y el debate entre las partes interesadas y los responsables de la toma de decisiones, así como para mejorar la gestión de los ecosistemas amenazados.

Knowledge graph based reasoning in medical image analysis: A scoping review.

Automated computer-aided diagnosis (CAD) is becoming more significant in the field of medicine due to advancements in computer hardware performance and the progress of artificial intelligence. The knowledge graph is a structure for visually representing knowledge facts. In the last decade, a large body of work based on knowledge graphs has effectively improved the organization and interpretability of large-scale complex knowledge. Introducing knowledge graph inference into CAD is a research direction with significant potential. In this review, we briefly review the basic principles and application methods of knowledge graphs firstly. Then, we systematically organize and analyze the research and application of knowledge graphs in medical imaging-assisted diagnosis. We also summarize the shortcomings of the current research, such as medical data barriers and deficiencies, low utilization of multimodal information, and weak interpretability. Finally, we propose future research directions with possibilities and potentials to address the shortcomings of current approaches.

Exploring teacher discourse patterns: Comparative insights from novice and expert teachers in junior high school EFL contexts.

Effective teacher discourse is critical in improving English as a foreign language (EFL) education, particularly in junior high schools in China, where students are at a crucial stage in their language development. As junior high school students are at a pivotal developmental stage, this research investigates the discourse patterns employed by novice and expert teachers to assess their impact on students' engagement and language acquisition. Despite the extensive research on teacher discourse in higher education, a significant gap remains regarding its application in compulsory primary education settings. This study aims to fill this gap by examining the current classroom discourse patterns of EFL teachers in junior high schools to identify the distinctions between novice and expert teachers and explore the factors contributing to these differences. This mixed-methods study includes qualitative and quantitative analyses. Verbatim transcriptions of six classes were used to create a corpus exceeding 20,000 words. The data were analysed using cross-tabulation in Excel and Chi-square tests in SPSS 22.0, complemented by semi-structured interviews with selected teachers. The theoretical framework is grounded in Long's（1996）interaction hypothesis, which underlines the significance of communication in facilitating language proficiency through meaningful interaction, and the analysis follows Sinclair and Coulthard's（1975）discourse patterns. The initiation-response-feedback (IRF) and initiation-response-0 (IR0) emerged as predominant patterns among both novice and expert teachers. Novice teachers predominantly relied on the basic IRF pattern, while expert teachers exhibited greater flexibility and more frequent use of variant patterns, such as IRFR, I[RnFn] and [InRn]F. Such adaptability among expert teachers creates a more interactive and engaging learning environment, thereby enhancing student participation and language acquisition. The study also identifies a novel variant structure, IRnF, used more frequently by expert teachers, underlining the benefits of group work in fostering teamwork and independent thinking. Expert teachers demonstrated a greater propensity to adapt their discourse strategies to foster a more production-oriented learning environment, which was the main factor driving the teachers' differing discourse patterns. This study significantly contributes to the analysis of teacher discourse in the junior high school EFL context, providing empirical evidence and practical insights that bridge the gap between theory and practice. By elucidating the distinct discourse practices of novice and expert teachers, this study offers valuable recommendations for teacher professional development and highlights the importance of employing varied and interactive discourse structures to improve EFL teaching effectiveness. The study also provides valuable insights for educators striving to improve their instructional practices and the language acquisition in EFL classrooms.

Medico-legal evaluation of occupational skin diseases and occupational skin cancer.

The medico-legal evaluation of occupational skin diseases is one of the core competencies of dermatology. As a neutral medical expert, the dermatologist has a different role to that of a treating physician. In Germany, the so-called Bamberg Recommendation (Bamberger Empfehlung) provides a scientifically based assessment basis to ensure equal treatment of all persons undergoing medico-legal evaluation. In addition to dermatological expertise, knowledge of insurance law and legal terminology is essential for the medical expert. Dermatologists provide legal and administrative decisions of social courts and social insurance institutions with their qualified expert opinions. In this way, dermatology makes an important contribution to social security.

Expert assessment of illegal collecting impacts on Venus flytraps and priorities for research on illegal trade.

Illegal collecting of wild Venus flytraps (Dionaea muscipula) for the horticultural trade represents a persistent threat to populations of the species across their endemic range in the coastal plain of North and South Carolina (United States). Although wild collecting of Venus flytraps is not a novel threat, there has been very little research on the impacts of collecting on the species' conservation to date or why an illegal trade persists alongside a legal one. We drew on qualitative expert stakeholder elicitation to contextualize the threat of illegal collecting to the long-term conservation of Venus flytraps in relation to other anthropogenic threats. Expert elicitation included botanical and conservation researchers, cognizant state and federal agency staff, land managers, and conservation nonprofit actors. The workshop included mapping of supply chain structures and prioritization of social and environmental harms. Expert consensus determined illegal collecting is an ongoing problem for Venus flytrap conservation, but habitat destruction, degradation, and fire suppression are the most significant threats to flytrap conservation. Supply chain analysis showed that observable social and environmental harms of the trade are focused at the supply stage and that less is known about transit and demand stages. Key research gaps identified include a lack of understanding of plant laundering practices relevant to a range of desirable plant taxa; the role of commercial nurseries in illicit horticultural supply chains; motivations for engaging in Venus flytrap collecting; and the persistent demand for illegally harvested plants when cultivated, legally obtainable plants are readily available. Our findings and methodology are relevant to a range of ornamental plants affected by illegal trade for which robust social data on illegal collecting drivers are lacking.

Evaluación experta del impacto de la colecta ilegal de venus atrapamoscas y las prioridades de investigación sobre el mercado ilegal Resumen La colecta ilegal de venus atrapamoscas (Dionaea muscipula) silvestres para el mercado de horticultura representa una amenaza constante para las poblaciones de la especie a lo largo de su distribución endémica en la planicie costera de Carolina del Norte y del Sur, Estados Unidos. Aunque esta colecta no es una amenaza novedosa, a la fecha se ha investigado muy poco sobre su impacto en la conservación de la especie o por qué el mercado ilegal persiste a la par del legal. Partimos del conocimiento cualitativo de los actores expertos para contextualizar la amenaza de la colecta ilegal para la conservación a largo plazo de la venus atrapamoscas en relación con otras amenazas antropogénicas. Este conocimiento involucró a investigadores de la conservación y la botánica, personal consciente de agencias federales y estatales y actores de la conservación sin fines de lucro. El taller incluyó el mapeo de las estructuras de las cadenas de suministro y la priorización de los daños sociales y ambientales. El consenso de los expertos determinó que la colecta ilegal es un problema continuo para la conservación de la venus atrapamoscas, pero la destrucción y degradación del hábitat, así como la contención de incendios son las amenazas más significativas. El análisis de las cadenas de suministro mostró que los daños ambientales y sociales observables en el mercado se enfocan en la fase de suministro y que se sabe poco sobre las fases de tránsito y demanda. Los vacíos de investigación más importantes incluyen la falta de entendimiento de las prácticas de lavado de plantas relevantes para un rango de taxones deseables de plantas; el papel de los viveros comerciales en las cadenas de suministro de la horticultura ilícita; los motivos para participar en la colecta de venus atrapamoscas; y la demanda continua de plantas cosechadas ilegalmente cuando ya hay disponibilidad de plantas cultivadas que se obtienen legalmente. Nuestros descubrimientos y metodología son relevantes para una gama de plantas ornamentales afectadas por el mercado ilegal para las cuales hay carencia de datos sociales sólidos sobre los factores de colecta ilegal.

A smart system for student performance assessment (SPA).

The proposed smart system for Student Performance Assessment (SPA) is a system that evaluates students' knowledge and skill attainment in a specific course by measuring their achievements of the Course Learning Outcomes (CLOs). The instructor defines the aspects, weights, and rating scale used by SPA to analyze each course. The system calculates the average of students' marks in each learning outcome and compares them with the CLO targets and scores to determine the effectiveness of the teaching and learning methods used. The system uses facts and rules extracted from the course syllabus and Bloom's Taxonomy to build its knowledge base. This paper presents the development of the SPA inference engine, which is used to find CLO targets based on the course level. The inference engine uses efficient procedures and a prediction process to determine the correct target and score, providing a reliable and understandable methodology for reasoning about the information in the knowledge base and formulating conclusions. SPA is a highly responsive and intelligent system that can be a valuable tool for measuring students' achievements. Its characteristics include high performance, reliability, and intelligibility, and its combination of cognitive systems and cognitive theory has led to remarkable progress in measuring student performance. Limitations include dependency on accurate course content and initial setup time, potential bias in CLO weight assignments, challenges in integrating SPA with existing institutional databases, the need for continuous updates to the knowledge base to reflect curriculum changes, and potential resistance from educators to adopt new technologies. Future improvements could involve adaptive learning integrations, enhanced user interfaces, and broader applicability across diverse educational settings.

Body fluid multiomics in 3PM-guided ischemic stroke management: health risk assessment, targeted protection against health-to-disease transition, and cost-effective personalized approach are envisaged.

Because of its rapid progression and frequently poor prognosis, stroke is the third major cause of death in Europe and the first one in China. Many independent studies demonstrated sufficient space for prevention interventions in the primary care of ischemic stroke defined as the most cost-effective protection of vulnerable subpopulations against health-to-disease transition. Although several studies identified molecular patterns specific for IS in body fluids, none of these approaches has yet been incorporated into IS treatment guidelines. The advantages and disadvantages of individual body fluids are thoroughly analyzed throughout the paper. For example, multiomics based on a minimally invasive approach utilizing blood and its components is recommended for real-time monitoring, due to the particularly high level of dynamics of the blood as a body system. On the other hand, tear fluid as a more stable system is recommended for a non-invasive and patient-friendly holistic approach appropriate for health risk assessment and innovative screening programs in cost-effective IS management. This article details aspects essential to promote the practical implementation of highlighted achievements in 3PM-guided IS management. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00376-2.

From guidelines to clinical practice in care for ischaemic stroke patients: A systematic review and expert opinion.

BACKGROUND AND PURPOSE: Guidelines help physicians to provide optimal care for stroke patients, but implementation is challenging due to the quantity of recommendations. Therefore a practical overview related to applicability of recommendations can be of assistance. METHODS: A systematic review was performed on ischaemic stroke guidelines published in scientific journals, covering the whole acute care process for patients with ischaemic stroke. After data extraction, experts rated the recommendations on dimensions of applicability, that is, actionability, feasibility and validity, on a 9-point Likert scale. Agreement was defined as a score of ≥8 by ≥80% of the experts. RESULTS: Eighteen articles were identified and 48 recommendations were ultimately extracted. Papers were included only if they described the whole acute care process for patients with ischaemic stroke. Data extraction and analysis revealed variation in terms of both content and comprehensiveness of this description. Experts reached agreement on 34 of 48 (70.8%) recommendations in the dimension actionability, for 16 (33.3%) in feasibility and for 15 (31.3%) in validity. Agreement on all three dimensions was reached for seven (14.6%) recommendations: use of a stroke unit, exclusion of intracerebral haemorrhage as differential diagnosis, administration of intravenous thrombolysis, performance of electrocardiography/cardiac evaluation, non-invasive vascular examination, deep venous thrombosis prophylaxis and administration of statins if needed. DISCUSSION AND CONCLUSION: Substantial variation in agreement was revealed on the three dimensions of the applicability of recommendations. This overview can guide stroke physicians in improving the care process and removing barriers where implementation may be hampered by validity and feasibility.

Structured over-the-counter medicine dataset to improve the safety of pharmaceuticals.

The Pharma-safe Index Dataset comprises comprehensive information on several aspects of pharmaceuticals, including general medication data, usage guidelines, dosage, adverse effects, pricing, drug interactions, duration of use, composition, and contraindications. The dataset is provided in both CSV and JSON file formats, and it is available in both English and Bahasa Indonesia. By conducting interviews, distributing flyers, and using pharmacy books, the dataset was collected from over-the-counter medications that were sold at three pharmacies located in Yogyakarta, Indonesia. A medical professional performed cleansing, standardization, and validation on it before it was exported to JSON and CSV formats. The data collected on drug efficacy, safety, and patient outcomes in Indonesia can be utilized by researchers in order to uncover trends and developing patterns of prescription drug resistance. It is possible that this will direct future research, lead to improvements in drug formulations, treatment strategies, and public health policies, and expand our understanding of how drugs work and how they affect patient health.

Delphi Technique on Nursing Competence Studies: A Scoping Review.

This scoping review was conducted under the Joanna Briggs Institute (JBI) framework. It included primary studies published until 30 April 2023, obtained through a systematic search across PubMed, Web of Science, CINAHL, and MEDLINE databases. The review focused on primary studies that used the Delphi technique in nursing competence research, especially those related to defining core competency frameworks and developing instruments to assess professional competence. The goal was to analyze the different methodological approaches used by authors, synthesize them, and propose recommendations to enhance methodological rigor, reliability, and validity in the application of the Delphi technique. For this purpose, the following review question was established: "What is the available evidence on the use of the Delphi technique in the study of professional competence in nursing?". The extracted textual elements underwent a content analysis, resulting in dimensions established through an inductive approach. Twenty studies were included, yielding insights into diverse methodological options for conducting Delphi studies, organised around a set of dimensions: (1) preparatory procedures; (2) procedures for accessing and selecting experts; (3) acquisition of expert input; (4) data analysis and consensus; and (5) ethical and legal procedures and guarantees. The study's limitations include the inability to include certain studies due to a lack of response to requests for clarification from corresponding authors. Additionally, the primary studies' methodological quality was not assessed, which is another relevant aspect. The study's results offer valuable insights for researchers intending to utilise the Delphi technique within the context of the research referenced in the included studies. This information encompasses important methodological choices, highlighting their potential benefits and associated risks. The review was prospectively registered on the Open Science Framework (Registration No: osf.io/kp2vw).

Experts' views on the implementation of digital interventions for eating disorders: a Delphi study.

BACKGROUND: Eating disorders (EDs) constitute a considerable burden for individuals and society, but adequate and timely professional treatment is rare. Evidence-based Digital Mental Health Interventions (DMHIs) have the potential both to reduce this treatment gap and to increase treatment effectiveness. However, their integration into routine care is lacking. Understanding practitioners' attitudes towards DMHIs for EDs is crucial for their effective use. AIMS: To investigate the consensus among German ED treatment experts on the relevance of different influencing factors for DMHI use in EDs. METHODS: This Delphi study consisted of two rounds and was conducted online with an initial sample of N = 24 ED experts (Mage=41.96, SDage=9.92, n = 22 female). Prior to the Delphi rounds, semi-structured qualitative telephone interviews were performed to explore participants' attitudes, experiences, and expectations towards DMHIs. In order to construct the Delphi survey, content analysis was applied to a subset of ten interviews. A total of 63 influencing factors were identified and grouped into three main categories: contextual conditions, design, and content of DMHIs. In both Delphi rounds, the interview participants were subsequently invited to rate each of the factors with regard to their importance on 10-point scales. Group percentages and individual ratings of the first round (n = 23) were presented in the second round (n = 21). Consensus was calculated for each item (defined as IQR ≤ 2). RESULTS: Importance ratings were high across items (M = 7.88, SD = 2.07, Mdn = 8). In the first round, 48% of the items reached consensus, with its most important (Mdn = 10) factors referring to data security, evidence base, technical requirements, usability, and specific DMHI content (psychoeducation, crisis intervention). In the second Delphi round, a consensus was reached on 73% of the items. No consensus was reached on 17 items. CONCLUSIONS: The findings on practitioners' attitudes and priorities have relevant implications for subsequent DMHI development, dissemination, and implementation strategies, indicating that the highest-rated factors should be highlighted in the process.

[Improvement of oral health of older people in hospitals: a scoping review]. / Verbesserung der Mundgesundheit älterer Menschen in Krankenhäusern: ein Scoping-Review.

BACKGROUND: The current evidence regarding interventions to improve oral health in older hospital patients is unclear. OBJECTIVE: This scoping review assesses the scope and nature of research activities and identifies gaps in the existing literature. METHODS: The inclusion criteria for this study included adults over the age of 65 years who were treated as inpatient outside of intensive care units and covered all interventions aimed at promoting oral health or hygiene. RESULTS: The systematic search yielded 12 final studies, focusing on oral healthcare interventions in various settings, primarily in high-income countries. The studies employed diverse designs including randomized controlled trials and prospective studies, with interventions mainly provided by multidisciplinary teams. The interventions aimed to improve oral health or prevent pneumonia. Overall, the studies highlighted a potential effectiveness of multidisciplinary approaches in improving oral health and preventing pneumonia in geriatric populations. CONCLUSION: This scoping review shows a limited and heterogeneous evidence base for oral health interventions for older patients in hospitals. The need for patient involvement is evident; however, there is often a lack of high-quality studies to draw robust conclusions.

Artificial intelligence for optimum tissue excision with indocyanine green fluorescence angiography for flap reconstructions: Proof of concept.

Background: Indocyanine green fluorescence angiography (ICGFA) is gaining popularity as an intraoperative tool to assess flap perfusion. However, it needs interpretation and there is concern regarding a potential for over-debridement with its use. Here we describe an artificial intelligence (AI) method that indicates the extent of flap trimming required. Methods: Operative ICGFA recordings from ten consenting patients undergoing flap reconstruction without subsequent partial/total necrosis as part of an approved prospective study (NCT04220242, Institutional Review Board Ref:1/378/2092), provided the training-testing datasets. Drawing from prior similar experience with ICGFA intestinal perfusion signal analysis, five fluorescence intensity and time-related features were analysed (MATLAB R2024a) from stabilised ICGFA imagery. Machine learning model training (with ten-fold cross-validation application) was grounded on the actual trimming by a consultant plastic surgeon (S.P.) experienced in ICGFA. MATLAB classification learner app was used to identify the most important feature and generate partial dependence plots for interpretability during training. Testing involved post-hoc application to unseen videos blinded to surgeon ICGFA interpretation. Results: Training:testing datasets comprised 7:3 ICGFA videos with 28 and 3 sampled lines respectively. Validation and testing accuracy were 99.9 % and 99.3 % respectively. Maximum fluorescence intensity identified as the most important predictive curve feature. Partial dependence plotting revealed a threshold of 22.1 grayscale units and regions with maximum intensity less then threshold being more likely to be predicted as "excise". Conclusion: The AI method proved discriminative regarding indicating whether to retain or excise peripheral flap portions. Additional prospective patients and expert references are needed to validate generalisability.

A Hybrid Framework for Maritime Surveillance: Detecting Illegal Activities through Vessel Behaviors and Expert Rules Fusion.

Maritime traffic is essential for global trade but faces significant challenges, including navigation safety, environmental protection, and the prevention of illicit activities. This work presents a framework for detecting illegal activities carried out by vessels, combining navigation behavior detection models with rules based on expert knowledge. Using synthetic and real datasets based on the Automatic Identification System (AIS), we structured our framework into five levels based on the Joint Directors of Laboratories (JDL) model, efficiently integrating data from multiple sources. Activities are classified into four categories: illegal fishing, suspicious activity, anomalous activity, and normal activity. To address the issue of a lack of labels and integrate data-driven detection with expert knowledge, we employed a stack ensemble model along with active learning. The results showed that the framework was highly effective, achieving 99% accuracy in detecting illegal fishing and 92% in detecting suspicious activities. Furthermore, it drastically reduced the need for manual checks by specialists, transforming experts' tacit knowledge into explicit knowledge through the models and allowing continuous updates of maritime domain rules. This work significantly contributes to maritime surveillance, offering a scalable and efficient solution for detecting illegal activities in the maritime domain.

A Uniform Approach for Advancing Athlete Assessment: A Tutorial on the Lens Model.

In athlete assessment, coaches or scouts typically judge athletes by observing and combining information about their attributes. However, how accurate is the expert's eye in combining this information, and can its accuracy be improved? To address these questions, this paper introduces the Lens Model, a framework for studying human judgment that has been widely successful in other performance domains. Since the framework offers both theoretical and practical benefits and is new to sports scientists and practitioners, our paper is presented in the form of a tutorial. First, we discuss the need for the Lens Model in sports; second, we demonstrate its proven value outside of sports. Third, we provide a conceptual explanation of the Lens Model, detailing, among other aspects, how experts' judgmental policies can be modeled and how judgmental accuracy can be determined and evaluated. This is followed by an empirical example: a study on the judgments of soccer scouts, along with suggestions to improve their accuracy. To inspire further Lens Model research across sports, we conclude with prospective research directions.

Instance segmentation of cells and nuclei from multi-organ cross-protocol microscopic images.

Background: Light microscopy is a widely used technique in cell biology due to its satisfactory resolution for cellular structure analysis, prevalent availability of fluorescent probes for staining, and compatibility for the dynamic analysis of live cells. However, the segmentation of cells and nuclei from microscopic images is not a straightforward process because it has several challenges such as high variation in morphology and shape, the presence of noise and diverse contrast in backgrounds, clustering or overlapping nature of cells. Dealing with these challenges and facilitating more reliable analysis necessitates the implementation of computer-aided methods that leverage image processing techniques and deep learning algorithms. The major goal of this study is to propose a model, for instance segmentation of cells and nuclei, applying the most cutting-edge deep learning techniques. Methods: A fine-tuned You Only Look at Once version 9 extended (YOLOv9-E) model is initially applied as a prompt generator to generate bounding box prompts. Using the generated prompts, a pre-trained segment anything model (SAM) is subsequently applied through zero-short inferencing to produce raw segmentation masks. These segmentation masks are then refined using non-max suppression and simple image processing methods such as image addition and morphological processing. The proposed method is developed and evaluated using an open-sourced dataset called Expert Visual Cell Annotation (EVICAN), which is relatively large and contains 4,738 microscopy images extracted from cross organs using different protocols. Results: Based on the evaluation results on three different levels of EVICAN test sets, the proposed method demonstrates noticeable performances showing average mAP50 [mean average precision at intersection over union (IoU) =0.50] scores of 96.25, 95.05, and 94.18 for cell segmentation, and 68.04, 54.66, and 38.29 for nucleus segmentation on easy, medium, and difficult test sets, respectively. Conclusions: Our proposed method for instance segmentation of cells and nuclei provided favorable performance compared to the existing methods in literature, indicating its potential utility as an assistive tool for cell culture experts, facilitating prompt and reliable analysis.

Expert Consensus on the Diagnosis and Management of Digoxin Toxicity.

While there has been a decline in the use of digoxin in patients with heart failure and atrial fibrillation, acute and chronic digoxin toxicity remains a significant clinical problem. Digoxin's narrow therapeutic window and nonspecific signs and symptoms of toxicity create clinical challenges and uncertainty around the diagnostic criteria of toxicity and responsive treatment choices for the bedside clinician. A systematic review of published literature on digoxin toxicity (34,587 publications over 6 decades, with 114 meeting inclusion criteria) was performed to develop 33 consensus statements on diagnostic and therapeutic approaches which were then evaluated through a modified Delphi process involving a panel of experts in cardiology, nursing, emergency medicine, and medical toxicology. The results demonstrate agreement about the need to consider time of ingestion and nature of the exposure (i.e. acute, acute-on-chronic, chronic) and the use of digoxin immune Fab for life-threatening exposure to decrease risk of death. While several areas of continued uncertainty were identified, this work offers formalized guidance that may help providers better manage this persistent clinical challenge.