Informatics innovation in clinical care: A visionary scenario for dentistry

Health information technology (HIT) is one of the most significant developments in health care in recent years. However, there is still a large gap between how HIT could support clinical work versus how it does. In this project, we developed a visionary scenario to identify opportunities for improving patient care in dentistry. In the scenario, patients and care providers are supported by a ubiquitous, embedded computing infrastructure that captures and processes data streams from multiple sources. Practical decision support, as well as automated background data processing (e.g., to screen for common conditions), helps clinicians provide quality care. A holistic view of clinical information technology (IT) focuses on supporting clinicians and patients in a user-centered manner. While clinical IT is still in very much a work in progress, scenarios such as the one presented may be helpful to keep us focused on the possibilities of tomorrow, not on the limitations of today

Decision support systems for adoption in dental clinics: a survey

While most dental clinicians use some sort of information system, they are involved with administrative functions, despite the advisory potential of some of these systems. This paper outlines some current decision support systems (DSS) and the common barriers facing dentists in adopting them within their workflow. These barriers include lack of perceived usefulness, complicated social and economic factors, and the difficulty for users to interpret the advice given by the system. A survey of current systems found that although there are systems that suggest treatment options, there is no real-time integration with other knowledge bases. Additionally, advice on drug prescription at point-of-care is absent from such systems, which is a significant omission, in consideration of the fact that disease management and drug prescription are common in the workflow of a dentist. This paper also addresses future trends in the research and development of dental clinical DSS, with specific emphasis on big data, standards and privacy issues to fulfil the vision of a robust, user-friendly and scalable personalised DSS for dentists. The findings of this study will offer strategies in design, research and development of a DSS with sufficient perceived usefulness to attract adoption and integration by dentists within their routine clinical workflow, thus resulting in better health outcomes for patients and increased productivity for the clinic

Nanorobotics in Medicine: A Systematic Review of Advances, Challenges, and Future Prospects

Nanorobotics offers an emerging frontier in biomedicine, holding the potential to revolutionize diagnostic and therapeutic applications through its unique capabilities in manipulating biological systems at the nanoscale. Following PRISMA guidelines, a comprehensive literature search was conducted using IEEE Xplore and PubMed databases, resulting in the identification and analysis of a total of 414 papers. The studies were filtered to include only those that addressed both nanorobotics and direct medical applications. Our analysis traces the technology's evolution, highlighting its growing prominence in medicine as evidenced by the increasing number of publications over time. Applications ranged from targeted drug delivery and single-cell manipulation to minimally invasive surgery and biosensing. Despite the promise, limitations such as biocompatibility, precise control, and ethical concerns were also identified. This review aims to offer a thorough overview of the state of nanorobotics in medicine, drawing attention to current challenges and opportunities, and providing directions for future research in this rapidly advancing field

Adult missing persons:a concept analysis

Missing persons incidents incur considerable societal costs but research has overwhelmingly concentrated on missing children. Understanding the phenomenon among adults is underdeveloped as a result. We conducted an evolutionary concept analysis of the ‘missing person’ in relation to adults. Evolutionary concept analysis provides a structured narrative review methodology which aims to clarify how poorly defined phenomena have been discussed in the professional/academic literature in order to promote conceptual clarity and provide building blocks for future theoretical development. A systematic literature search identified k = 73 relevant papers from which surrogate terms for, and antecedents, consequences, and attributes of the occurrence of adult missing persons were extracted and analysed. The core attributes of the adult missing person are (i) actual or perceived unexpected or unwanted absence accompanied by an absence of information and (ii) a potential adverse risk outcome as perceived by those left behind. The centrality of mental ill-health in actual adult missing persons cases is not reflected in theoretical development which largely comprises descriptive typologies of variable quality and questionable utility. There is a clear need to shift research emphasis towards clinical and psychological domains of inquiry in order to further advance the field of adult missing persons research

The reliability of cephalometric tracing using AI

Introduction : L'objectif de cette étude est de comparer la différence entre l'analyse céphalométrique manuelle et l'analyse automatisée par l’intelligence artificielle afin de confirmer la fiabilité de cette dernière. Notre hypothèse de recherche est que la technique manuelle est la plus fiable des deux méthodes. Méthode : Un total de 99 radiographies céphalométriques latérales sont recueillies. Des tracés par technique manuelle (MT) et par localisation automatisée par intelligence artificielle (AI) sont réalisés pour toutes les radiographies. La localisation de 29 points céphalométriques couramment utilisés est comparée entre les deux groupes. L'erreur radiale moyenne (MRE) et un taux de détection réussie (SDR) de 2 mm sont utilisés pour comparer les deux groupes. Le logiciel AudaxCeph version 6.2.57.4225 est utilisé pour l'analyse manuelle et l'analyse AI. Résultats : Le MRE et SDR pour le test de fiabilité inter-examinateur sont respectivement de 0,87 ± 0,61mm et 95%. Pour la comparaison entre la technique manuelle MT et le repérage par intelligence artificielle AI, le MRE et SDR pour tous les repères sont respectivement de 1,48 ± 1,42 mm et 78 %. Lorsque les repères dentaires sont exclus, le MRE diminue à 1,33 ± 1,39 mm et le SDR augmente à 84 %. Lorsque seuls les repères des tissus durs sont inclus (excluant les points des tissus mous et dentaires), le MRE diminue encore à 1,25 ± 1,09 mm et le SDR augmente à 85 %. Lorsque seuls les points de repère des tissus mous sont inclus, le MRE augmente à 1,68 ± 1,89 mm et le SDR diminue à 78 %. Conclusion: La performance du logiciel est similaire à celles précédemment rapportée dans la littérature pour des logiciels utilisant un cadre de modélisation similaire. Nos résultats révèlent que le repérage manuel a donné lieu à une plus grande précision. Le logiciel a obtenu de très bons résultats pour les points de tissus durs, mais sa précision a diminué pour les tissus mous et dentaires. Nous concluons que cette technologie est très prometteuse pour une application en milieu clinique sous la supervision du docteur.Introduction: The objective of this study is to compare the difference between manual cephalometric analysis and automatic analysis by artificial intelligence to confirm the reliability of the latter. Our research hypothesis is that the manual technique is the most reliable of the methods and is still considered the gold standard. Method: A total of 99 lateral cephalometric radiographs were collected in this study. Manual technique (MT) and automatic localization by artificial intelligence (AI) tracings were performed for all radiographs. The localization of 29 commonly used landmarks were compared between both groups. Mean radial error (MRE) and a successful detection rate (SDR) of 2mm were used to compare both groups. AudaxCeph software version 6.2.57.4225 (Audax d.o.o., Ljubljana, Slovenia) was used for both manual and AI analysis. Results: The MRE and SDR for the inter-examinator reliability test were 0.87 ± 0.61mm and 95% respectively. For the comparison between the manual technique MT and landmarking with artificial intelligence AI, the MRE and SDR for all landmarks were 1.48 ± 1.42mm and 78% respectively. When dental landmarks are excluded, the MRE decreases to 1.33 ± 1.39mm and the SDR increases to 84%. When only hard tissue landmarks are included (excluding soft tissue and dental points) the MRE decreases further to 1.25 ± 1.09mm and the SDR increases to 85%. When only soft tissue landmarks are included the MRE increases to 1.68 ± 1.89mm and the SDR decreases to 78%. Conclusion: The software performed similarly to what was previously reported in literature for software that use analogous modeling framework. Comparing the software’s landmarking to manual landmarking our results reveal that the manual landmarking resulted in higher accuracy. The software operated very well for hard tissue points, but its accuracy went down for soft and dental tissue. Our conclusion is this technology shows great promise for application in clinical settings under the doctor’s supervision

Determination of the informational content of symptoms in the dynamic processes of assessing the patient’s condition in e-health

The study is devoted to substantiating the tactics of choosing the signs of the patient's condition for diagnostic decision-making on corrective medical intervention in mobile medicine. The aim of the research: to study a creation of a methodology for determining the integral informativeness of the patient's symptoms during remote monitoring of his condition. Materials and methods: this article is based on search results in PubMed, Scopus, MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA articles published between January 1991 and January 2021 and containing the search terms “information technology”, “Mobile medicine”, “digital pathology” and “deep learning”, as well as the results of the authors' own research. The authors independently extracted data on concealment of distribution, consistency of distribution, blindness, completeness of follow-up, and interventions. Results: concluded that to determine the Informativeness of symptoms in mobile monitoring of patients, it is possible to use risk indicators of predicted conditions as a universal method. Given that the Informativeness of the patient's condition changes constantly, for online diagnosis of conditions during remote monitoring of the patient it is recommended to use the function of informative symptoms from time to time and use a set of approaches to assess the Informativeness of patient symptoms. It is proposed to use the strategy of diagnosis and treatment using probabilistic algorithms based on the values of the risk of complications of the pathological process, as well as the formulas of Kulbach and Shannon to determine individual trends in the pathological patient process. Conclusion: there was proposed to use risk indicators of predicted conditions as a universal method for determining the informational content of symptoms in mobile monitoring of patients

Mobility and Cognition in Seniors. Report from the 2008 Institute of Aging (CIHR) Mobility and Cognition Workshop

Background The annual Scientific Meeting of the Canadian Association on Gerontology was held on October 24 and 25, 2008 in London, Ontario. Prior to the annual meeting, mobility and cognition experts met on October 23, 2008 to engage in a pre-conference workshop. Methods Discussions during the workshop addressed novel areas of research and knowledge and research gaps pertaining to the interaction between mobility and cognition in seniors. Results Workshop presenters moved from the neuromuscular, biomechanics, and neurology of gait impairments, and falls through the role of cognition and mood on mobility regulation to the whole person in the environment. Research gaps were identified. Conclusions Despite a consensus that mobility and cognition are increasingly correlated as people age, several gaps in our understanding of mechanisms and how to assess the interaction were recognized. The gaps originally identified in 2008 are still pertinent today. Common and standardized assessments for “mobility and cognition” are still not in place in current practice. Interventions that target mobility and cognitive decline as a single entity are still lacking