AI as a Medical Device Adverse Event Reporting in Regulatory Databases: Protocol for a Systematic Review.

BACKGROUND: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack of knowledge of how to report AEs, and a general culture of nonreporting. The introduction of artificial intelligence as a medical device (AIaMD) requires a robust safety monitoring environment that recognizes both generic risks of a medical device and some of the increasingly recognized risks of AIaMD (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems and explore potential mechanisms for how AEs could be detected, attributed, and reported with a view to improving the early detection of safety signals. OBJECTIVE: The systematic review outlined in this protocol aims to yield insights into the frequency and severity of AEs while characterizing the events using existing regulatory guidance. METHODS: Publicly accessible AE databases will be searched to identify AE reports for AIaMD. Scoping searches have identified 3 regulatory territories for which public access to AE reports is provided: the United States, the United Kingdom, and Australia. AEs will be included for analysis if an artificial intelligence (AI) medical device is involved. Software as a medical device without AI is not within the scope of this review. Data extraction will be conducted using a data extraction tool designed for this review and will be done independently by AUK and a second reviewer. Descriptive analysis will be conducted to identify the types of AEs being reported, and their frequency, for different types of AIaMD. AEs will be analyzed and characterized according to existing regulatory guidance. RESULTS: Scoping searches are being conducted with screening to begin in April 2024. Data extraction and synthesis will commence in May 2024, with planned completion by August 2024. The review will highlight the types of AEs being reported for different types of AI medical devices and where the gaps are. It is anticipated that there will be particularly low rates of reporting for indirect harms associated with AIaMD. CONCLUSIONS: To our knowledge, this will be the first systematic review of 3 different regulatory sources reporting AEs associated with AIaMD. The review will focus on real-world evidence, which brings certain limitations, compounded by the opacity of regulatory databases generally. The review will outline the characteristics and frequency of AEs reported for AIaMD and help regulators and policy makers to continue developing robust safety monitoring processes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48156.

Performance Assessment of Universal Machine Learning Interatomic Potentials: Challenges and Directions for Materials' Surfaces.

Machine learning interatomic potentials (MLIPs) are one of the main techniques in the materials science toolbox, able to bridge ab initio accuracy with the computational efficiency of classical force fields. This allows simulations ranging from atoms, molecules, and biosystems, to solid and bulk materials, surfaces, nanomaterials, and their interfaces and complex interactions. A recent class of advanced MLIPs, which use equivariant representations and deep graph neural networks, is known as universal models. These models are proposed as foundation models suitable for any system, covering most elements from the periodic table. Current universal MLIPs (UIPs) have been trained with the largest consistent data set available nowadays. However, these are composed mostly of bulk materials' DFT calculations. In this article, we assess the universality of all openly available UIPs, namely MACE, CHGNet, and M3GNet, in a representative task of generalization: calculation of surface energies. We find that the out-of-the-box foundation models have significant shortcomings in this task, with errors correlated to the total energy of surface simulations, having an out-of-domain distance from the training data set. Our results show that while UIPs are an efficient starting point for fine-tuning specialized models, we envision the potential of increasing the coverage of the materials space toward universal training data sets for MLIPs.

Disruption, transformation and silos: medical humanities and the management gurus.

To disrupt, to transform and to break through silos are common sense aims for the medical humanities and other interdisciplinary endeavours. These keywords arise because of the influence upon the academy of management and business gurus, reputed experts who arose in response to the economic crises of the 1980s. Despite the noted analytic deficiencies in the concept of disruption, and its association with product innovation, the term has been extended to academic research, where it connotes radical novelty in research practice, typically accompanied by profound organisational and managerial change. 'Disruption' has become wedded to the word 'transformation' as national funders seek to support more radically innovative research that will maintain Western economic hegemony. A distorted version of Kuhn's model of scientific revolutions underpins the discourse of transformation, which fits humanities research to a template in which revolutionary, transformative shifts can be instrumentally favoured by funders, at the expense of inferior 'incremental' progress. Disruptive and transformative research are, according to funders, more readily produced in organisations that have broken through silos between disciplines. The silo metaphor misleadingly models academic disciplines as if they were essentially unitary entities, akin to the functionally specialised units of a business organisation. The discourse of silos arises from the guru doctrine of the learning organisation. This theory supposes that the organisation-including the university-is literally a living organism, and thereby susceptible to corporate sickness, mortality, infection and disability. Medical humanity researchers should be aware of, and reject, this vitalist metaphysic in which the optimal organisation is a culturally homogeneous supra-personal organism whose immense capacities are harnessed by visionary leaders. Moreover, a new vocabulary should be developed for research evaluation, superseding the supposed hierarchical opposition between transformative and incremental research.

On the use of the term "real risk".

The term "real risk" and variations of this term are commonly used in everyday speech and writing, and in the scientific literature. There are mainly two types of use: i) in statements about what the real risk related to an activity is and ii) in statements about the risk related to an activity being real. The former type of use has been extensively discussed in the literature, whereas the latter type has received less attention. In the present study, we review both types of use and analyze and discuss potential meanings of type ii) statements. We conclude that it is reasonable to interpret a statement about the risk being real as reflecting a judgement that there is some risk and that the knowledge supporting this statement is relatively strong. However, such a statement does not convey whether the risk is small or large and needs to be supplemented by a characterization of the risk.

Who, What, Where, and How? The State of Family Science in Pediatric Palliative Care.

CONTEXT: Families are vital providers and recipients of pediatric palliative care (PPC) services. Understanding the scope and nature of evidence at the intersection of family science and PPC research is necessary to develop family-focused interventions that enhance child and family health. OBJECTIVES: Explore and describe the family-level impact of pediatric serious illness. METHODS: We conducted a librarian-assisted scoping review using Arskey and O'Malley's approach. We searched PubMed, Scopus, CINAHL, and EMBASE databases for empirical publications from 2016-2021 that focused on families navigating serious pediatric illness published in English. Two reviewers assessed eligibility, with discrepancies resolved by a third. We used Covidence and REDCap for data management and extraction. RESULTS: We screened 10,983 abstracts; 309 abstracts were included in full text screening. The final group of 52 citations was analyzed by the entire team. Most research was conducted in Western Europe and North America. The perspectives of parents of children with cancer were most frequently described; voices of seriously ill youth and their siblings were less often presented. Most of the research was descriptive qualitative, followed by descriptive quantitative. Few studies were mixed methods, inferential, or interpretive. Studies most often described parent, youth, and family experience with illness and less often explored family processes and relationships. Irrespective of the approach (i.e., qualitative, quantitative), few studies focused on families as the analytic unit or used family-level analysis techniques. Study participants were usually from local dominant populations and less often from historically marginalized communities. CONCLUSION: The robust, descriptive, and individual-level evidence describing family impact of serious pediatric illness provides a solid foundation for future research priorities. Stronger integration of family techniques and diverse family voices in pediatric palliative care research can clarify family processes, illuminate structural barriers, and inform interventions that are responsive to family needs. These steps will enhance the education, policy, and clinical provision of PPC to all who would benefit, thereby advancing health equity for children living with serious illness and their families.

The Cannabis Gray Market: A Case for Cannabis Regulatory Science Research.

The cannabis gray market poses significant public health concerns and remains a major threat to consumer and/or potential consumer uptake of regulated cannabis markets in jurisdictions with legal state-sponsored cannabis programs. In this perspective, we provide an overview of the cannabis gray market, and describe an integrated epidemiological and regulatory science framework to study the gray market. Using tobacco regulatory science as a guide, we introduce example cannabis regulatory science research activities as a means to improve the field's understanding of the cannabis gray market. Cannabis regulatory science is a developing field that can improve our understanding of the cannabis regulatory ecosystem and provide regulatory officials and policymakers alike with much needed data to inform regulatory decision-making and improve the success and uptake of state-sponsored cannabis programs.

Barriers and facilitators influencing implementation of care technology for people with intellectual disabilities: A cross-sectional study among care professionals.

BACKGROUND: Implementation issues often hinder reaching the potential of care technology to improve daily lives of people with intellectual disabilities. We investigated barriers to and facilitators of implementing different technology modalities (app/social robot/sensor/domotics) in long-term care. METHOD: Care professionals (N = 83) from 12 Dutch disability care organisations completed a customised measurement instrument for determinants of innovations (MIDI) questionnaire. RESULTS: Out of 27 determinants, 20 were identified as facilitators and 16 as barriers. We highlight common barriers: few colleagues who work with the technology; no (awareness of) formal ratification of technology use; no arrangements regarding turnover of staff using the technology; unsettling organisational changes; technological defects and limited IT preconditions. CONCLUSIONS: The results, which could be combined and compared across study sites, provide insight into which implementation determinants were already well addressed, and where there is ground to gain when implementing care technology in disability care organisations.

Endocrine Entropy.

This communication defines and describes the novel concept of endocrine entropy. The authors share insights regarding the various facets of entropy in endocrine epidemiology, physiology, clinical presentation and management. The discussion opens up a new way of approaching endocrinology. Recent advances in artificial intelligence, assessment and addressal of entropy may become integral part of endocrine diagnostics and therapeutics.

Endocrine Entropy.

This communication defines and describes the novel concept of endocrine entropy. The authors share insights regarding the various facets of entropy in endocrine epidemiology, physiology, clinical presentation and management. The discussion opens up a new way of approaching endocrinology. Recent advances in artificial intelligence, assessment and addressal of entropy may become integral part of endocrine diagnostics and therapeutics.

Ethics and applications of isotope analysis in archaeology.

This synthesis explores specific ethical questions that commonly arise in isotopic analysis. For more than four decades, isotope analysis has been employed in archeological studies to explore past human and animal dietary habits, mobility patterns, and the environment in which a human or animal inhabited during life. These analyses require consideration of ethical issues. While theoretical concepts are discussed, we focus on practical aspects: working with descendant communities and other rights holders, choosing methods, creating and sharing data, and working mindfully within academia. These layers of respect and care should surround our science. This paper is relevant for specialists in isotope analysis as well as those incorporating these methods into larger projects. By covering the whole of the research process, from design to output management, we appeal broadly to archaeology and provide actionable solutions that build on the discussions in the general field.

Clinician Perspectives on Suicide Safety Planning and Its Implementation.

OBJECTIVE: The safety planning intervention is an evidence-based practice shown to reduce suicide risk, but implementation of high-quality safety planning has proven challenging. We aimed to understand clinician perspectives on the safety planning intervention to inform future implementation efforts. METHOD: This cross-sectional survey of clinicians who care for patients at risk of suicide in an academic medical center asked about comfort levels and fidelity to components of the safety planning intervention and assessed implementation barriers and facilitators. We used exploratory data analysis and regression analysis to explore clinician perspectives and assess the relationship between formal training and implementation. RESULTS: Ninety-two clinicians responded to the survey. Two-thirds of participants (64.9%) endorsed using all six core elements of the safety planning intervention. Participants who reported receiving formal training in safety planning were significantly more likely to report being comfortable completing a safety plan (p < .001); those with higher levels of comfort were significantly more likely to endorse using all of the core elements of the safety planning intervention (p < .001). CONCLUSIONS: Training in the evidence-based safety planning intervention is associated with clinician comfort and awareness of the core elements of the intervention. Our results suggest that there are gaps in clinician training and that formal safety planning intervention training could have a positive effect on clinician comfort and treatment fidelity.

ARBUR, a machine learning-based analysis system for relating behaviors and ultrasonic vocalizations of rats.

Deciphering how different behaviors and ultrasonic vocalizations (USVs) of rats interact can yield insights into the neural basis of social interaction. However, the behavior-vocalization interplay of rats remains elusive because of the challenges of relating the two communication media in complex social contexts. Here, we propose a machine learning-based analysis system (ARBUR) that can cluster without bias both non-step (continuous) and step USVs, hierarchically detect eight types of behavior of two freely behaving rats with high accuracy, and locate the vocal rat in 3-D space. ARBUR reveals that rats communicate via distinct USVs during different behaviors. Moreover, we show that ARBUR can indicate findings that are long neglected by former manual analysis, especially regarding the non-continuous USVs during easy-to-confuse social behaviors. This work could help mechanistically understand the behavior-vocalization interplay of rats and highlights the potential of machine learning algorithms in automatic animal behavioral and acoustic analysis.

Path analysis for controlling climate change in global aviation.

The aviation industry's emissions have had a significant impact on global climate change. This study focuses on carbon emission trading schemes, sustainable aviation fuels (SAFs), and hydrogen energy, as vital means for the aviation industry to reduce emissions. To evaluate the climate effects of global routes under four scenarios (24 sub-scenarios) until 2100, this study proposes the Aviation-FAIR (Aviation-Finite Amplitude Impulse Response) method. The findings reveal that while CO2 emissions and concentrations are significant, other emissions, such as N2O and CH4, have a greater effective radiative forcing (ERF) and contribute significantly to climate change. Moreover, SAFs are more effective in mitigating airline pollutant emissions than relying solely on carbon trading schemes. The effectiveness of hydrogen fuel cells may be hindered by technical limitations compared to hydrogen turbine engines. The findings of this study provide reference for the global aviation industry to adopt emission reduction measures.

The role of social media in public health awareness during times of war in Sudan: snakebites and scorpion stings.

BACKGROUND: Snakebite envenomation (SBE) and scorpion sting envenomation (SSE) are significant neglected tropical diseases that primarily affect impoverished communities in rural areas of developing nations. A lack of understanding about snake and scorpion species and their distribution exacerbates the disabilities and fatalities caused by SBE and SSE. In Sudan, particularly in regions affected by ongoing conflicts where healthcare resources are scarce, social media platforms offer a cost-effective approach to addressing public health challenges. Our aim in this study is to highlight the benefits of using social media for data collection and health promotion in such environments. METHODS: We present a cost-effective communication and data collection strategy implemented at the Toxic Organisms Research Centre (TORC) of the University of Khartoum, focusing on a Facebook group, "Scorpions and Snakes of Sudan", as our primary social media platform. Additionally, we discuss the lessons learned and the initial impact of this strategy on enhancing population health literacy. RESULTS: The group community is composed of ~ 5000 members from 14 countries. During the period from January 2023 to January 2024, we received 417 enquiries about snakes and scorpions belonging to 11 families and composed of 55 species. In addition, 53 other enquiries covered a range of organisms and their tracks (e.g., spiders, skinks, chameleons, foxes, sun spiders, centipedes, lizards, moth larvae, and insect tracks). The first photographic evidence of Malpolon monspessulanus in Sudan was via the group activities. The rare species Telescopus gezirae, the Blue Nile cat snake, is also documented via the group member's queries. Recognizing the evolving nature of social media use in public health, we also address the current limitations and evidence gaps that need to be addressed to effectively translate best practices into policy. CONCLUSION: In conclusion, utilizing Facebook as an institutional platform to share scientific information in simple Arabic language underscores the proactive roles that citizens, scientists, and public health stakeholders can play in leveraging social media for eHealth, eAwareness, and public health initiatives. This approach highlights the potential for collaborative efforts, particularly during crises, to maximize the benefits of social media in advancing public health.

Traditional healer support to improve HIV viral suppression in rural Uganda (Omuyambi): study protocol for a cluster randomized hybrid effectiveness-implementation trial.

BACKGROUND: Rural African people living with HIV face significant challenges in entering and remaining in HIV care. In rural Uganda, for example, there is a threefold higher prevalence of HIV compared to the national average and lower engagement throughout the HIV continuum of care. There is an urgent need for appropriate interventions to improve entry and retention in HIV care for rural Ugandans with HIV. Though many adults living with HIV in rural areas prioritize seeking care services from traditional healers over formal clinical services, healers have not been integrated into HIV care programs. The Omuyambi trial is investigating the effectiveness of psychosocial support delivered by traditional healers as an adjunct to standard HIV care versus standard clinic-based HIV care alone. Additionally, we are evaluating the implementation process and outcomes, following the Consolidated Framework for Implementation Research. METHODS: This cluster randomized hybrid type 1 effectiveness-implementation trial will be conducted among 44 traditional healers in two districts of southwestern Uganda. Healers were randomized 1:1 into study arms, where healers in the intervention arm will provide 12 months of psychosocial support to adults with unsuppressed HIV viral loads receiving care at their practices. A total of 650 adults with unsuppressed HIV viral loads will be recruited from healer clusters in the Mbarara and Rwampara districts. The primary study outcome is HIV viral load measured at 12 months after enrollment, which will be analyzed by intention-to-treat. Secondary clinical outcome measures include (re)initiation of HIV care, antiretroviral therapy adherence, and retention in care. The implementation outcomes of adoption, fidelity, appropriateness, and acceptability will be evaluated through key informant interviews and structured surveys at baseline, 3, 9, 12, and 24 months. Sustainability will be measured through HIV viral load measurements at 24 months following enrollment. DISCUSSION: The Omuyambi trial is evaluating an approach that could improve HIV outcomes by incorporating previously overlooked community lay supporters into the HIV cascade of care. These findings could provide effectiveness and implementation evidence to guide the development of policies and programs aimed at improving HIV outcomes in rural Uganda and other countries where healers play an essential role in community health. TRIAL REGISTRATION: ClinicalTrials.gov NCT05943548. Registered on July 5, 2023. The current protocol version is 4.0 (September 29, 2023).

Application of machine reading comprehension techniques for named entity recognition in materials science.

Materials science is an interdisciplinary field that studies the properties, structures, and behaviors of different materials. A large amount of scientific literature contains rich knowledge in the field of materials science, but manually analyzing these papers to find material-related data is a daunting task. In information processing, named entity recognition (NER) plays a crucial role as it can automatically extract entities in the field of materials science, which have significant value in tasks such as building knowledge graphs. The typically used sequence labeling methods for traditional named entity recognition in material science (MatNER) tasks often fail to fully utilize the semantic information in the dataset and cannot effectively extract nested entities. Herein, we proposed to convert the sequence labeling task into a machine reading comprehension (MRC) task. MRC method effectively can solve the challenge of extracting multiple overlapping entities by transforming it into the form of answering multiple independent questions. Moreover, the MRC framework allows for a more comprehensive understanding of the contextual information and semantic relationships within materials science literature, by integrating prior knowledge from queries. State-of-the-art (SOTA) performance was achieved on the Matscholar, BC4CHEMD, NLMChem, SOFC, and SOFC-Slot datasets, with F1-scores of 89.64%, 94.30%, 85.89%, 85.95%, and 71.73%, respectively in MRC approach. By effectively utilizing semantic information and extracting nested entities, this approach holds great significance for knowledge extraction and data analysis in the field of materials science, and thus accelerating the development of material science.Scientific contributionWe have developed an innovative NER method that enhances the efficiency and accuracy of automatic entity extraction in the field of materials science by transforming the sequence labeling task into a MRC task, this approach provides robust support for constructing knowledge graphs and other data analysis tasks.

A bibliometric analysis of speech and language impairments in Parkinson's disease based on Web of Science.

Many individuals with Parkinson's disease suffer from speech and language impairments that significantly impact their quality of life. Despite several studies on these disorders, there is a lack of relevant bibliometric analyses. This paper conducted a bibliometric analysis of 3,610 papers on speech and language impairments in Parkinson's disease patients from January 1961 to November 2023, based on the Web of Science Core Collection database. Using Citespace software, the analysis focused on annual publication volume, cooperation among countries and institutions, author collaborations, journals, co-citation references, and keywords, aiming to explore the current research status, hotspots, and frontiers in this field. The number of annual publications related to speech and language impairment in Parkinson's disease have been increasing over the years. The USA leads in the number of publications. Research hotspots include the mechanism underlying speech and language impairments, clinical symptoms, automated diagnosis and classification of patients with PD using linguistic makers, and rehabilitation interventions.

Implementation of a virtual, shared medical appointment program that focuses on food as medicine principles in a population with obesity: the SLIM program.

Background: Multimodal lifestyle interventions, employing food as medicine, stand as the recommended first-line treatment for obesity. The Shared Medical Appointment (SMA) model, where a physician conducts educational sessions with a group of patients sharing a common diagnosis, offers an avenue for delivery of comprehensive obesity care within clinical settings. SMAs, however, are not without implementation challenges. We aim to detail our experience with three implementation models in launching a virtual integrative health SMA for weight management. Methods: Eligible patients included individuals 18 years of age or older, having a body mass index (BMI) of 30 kg/m2 or 27 kg/m2 or greater with at least one weight related comorbidity. The Practical, Robust Implementation and Sustainability Model (PRISM), Plan, Do, Study, Act (PDSA), and the Framework for Reporting Adaptations and Modifications-Enhanced (FRAME) models were applied to guide the implementation of the Supervised Lifestyle Integrative Medicine (SLIM) program, a virtually delivered, lifestyle medicine focused SMA program, in a weight management clinic within a major health system. We describe how these models, along with attendance for the initial cohorts, were used for decision-making in the process of optimizing the program. Results: 172 patients completed the SLIM program over two years. Attendance was lowest for sessions held at 8:00 AM and 4:00 PM compared to sessions at 10:00 AM, 1:00 PM, and 3:00 PM, leading to only offering midday sessions (p = 0.032). Attendance data along with feedback from patients, facilitators, and administrative partners led to changes in the curriculum, session number and frequency, session reminder format, and intake visit number. Conclusion: The use of implementation and quality improvement models provided crucial insight for deployment and optimization of a virtual, lifestyle medicine focused SMA program for weight management within a large healthcare system.