NVIDIA's "Chat with RTX" Custom Large Language Model and Personalized AI Chatbot Augments the Value of Electronic Dermatology Reference Material.

This paper demonstrates a new, promising method using generative artificial intelligence (AI) to augment the educational value of electronic textbooks and research papers (locally stored on user's machine) and maximize their potential for self-study, in a way that goes beyond the standard electronic search and indexing that is already available in all of these textbooks and files. The presented method runs fully locally on the user's machine, is generally affordable, and does not require high technical expertise to set up and customize with the user's own content.

Health Digital Twins in Life Science and Health Care Innovation.

Health digital twins (HDTs) are virtual representations of real individuals that can be used to simulate human physiology, disease, and drug effects. HDTs can be used to improve drug discovery and development by providing a data-driven approach to inform target selection, drug delivery, and design of clinical trials. HDTs also offer new applications into precision therapies and clinical decision making. The deployment of HDTs at scale could bring a precision approach to public health monitoring and intervention. Next steps include challenges such as addressing socioeconomic barriers and ensuring the representativeness of the technology based on the training and validation data sets. Governance and regulation of HDT technology are still in the early stages.

Modelling the Predictors of Mobile Health (mHealth) Adoption among Healthcare Professionals in Low-Resource Environments.

This study was conducted with objectives to measure and validate the unified theory of the acceptance and use of technology (UTAUT) model as well as to identify the predictors of mobile health (mHealth) technology adoption among healthcare professionals in limited-resource settings. A cross-sectional survey was conducted at the six public and private hospitals in the two districts (Lodhran and Multan) of Punjab, Pakistan. The participants of the study comprised healthcare professionals (registered doctors and nurses) working in the participating hospitals. The findings of the seven-factor measurement model showed that behavioral intention (BI) to mHealth adoption is significantly influenced by performance expectancy (ß = 0.504, CR = 5.064, p < 0.05) and self-concept (ß = 0.860, CR = 5.968, p < 0.05) about mHealth technologies. The findings of the structural equation model (SEM) showed that the model is acceptable (χ2 (df = 259) = 3.207; p = 0.000; CFI = 0.891, IFI = 0.892, TLI = 0.874, RMSEA = 0.084). This study suggests that the adoption of mHealth can significantly help in improving people's access to quality healthcare resources and services as well as help in reducing costs and improving healthcare services. This study is significant in terms of identifying the predictors that play a determining role in the adoption of mHealth among healthcare professionals. This study presents an evidence-based model that provides an insight to policymakers, health organizations, governments, and political leaders in terms of facilitating, promoting, and implementing mHealth adoption plans in low-resource settings, which can significantly reduce health disparities and have a direct impact on health promotion.

ChatGPT in Clinical Toxicology.

ChatGPT has recently been shown to pass the United States Medical Licensing Examination (USMLE). We tested ChatGPT (Feb 13, 2023 release) using a typical clinical toxicology case of acute organophosphate poisoning. ChatGPT fared well in answering all of our queries regarding it.

Geospatial techniques for monitoring and mitigating climate change and its effects on human health.

This article begins by briefly examining the multitude of ways in which climate and climate change affect human health and wellbeing. It then proceeds to present a quick overview of how geospatial data, methods and tools are playing key roles in the measurement, analysis and modelling of climate change and its effects on human health. Geospatial techniques are proving indispensable for making more accurate assessments and estimates, predicting future trends more reliably, and devising more optimised climate change adaptation and mitigation plans.

Privacy-by-Design Environments for Large-Scale Health Research and Federated Learning from Data.

This article offers a brief overview of 'privacy-by-design (or data-protection-by-design) research environments', namely Trusted Research Environments (TREs, most commonly used in the United Kingdom) and Personal Health Trains (PHTs, most commonly used in mainland Europe). These secure environments are designed to enable the safe analysis of multiple, linked (and often big) data sources, including sensitive personal data and data owned by, and distributed across, different institutions. They take data protection and privacy requirements into account from the very start (conception phase, during system design) rather than as an afterthought or 'patch' implemented at a later stage on top of an existing environment. TREs and PHTs are becoming increasingly important for conducting large-scale privacy-preserving health research and for enabling federated learning and discoveries from big healthcare datasets. The paper also presents select examples of successful TRE and PHT implementations and of large-scale studies that used them.

Reconciling public health common good and individual privacy: new methods and issues in geoprivacy.

This article provides a state-of-the-art summary of location privacy issues and geoprivacy-preserving methods in public health interventions and health research involving disaggregate geographic data about individuals. Synthetic data generation (from real data using machine learning) is discussed in detail as a promising privacy-preserving approach. To fully achieve their goals, privacy-preserving methods should form part of a wider comprehensive socio-technical framework for the appropriate disclosure, use and dissemination of data containing personal identifiable information. Select highlights are also presented from a related December 2021 AAG (American Association of Geographers) webinar that explored ethical and other issues surrounding the use of geospatial data to address public health issues during challenging crises, such as the COVID-19 pandemic.

Integrating Social and Family Support as a Measure of Health Outcomes: Validity Implications from the Integrated Model of Health Literacy.

(1) Background: Health literacy (HL) is one of the key determinants of health and healthcare outcomes. The objectives of this study are to measure and validate Sørensen et al.'s integrated model of health literacy (IMHL) in a developing country's youth population, as well as to assess the impact of family affluence and social and family support on healthcare domains. (2) Methods: A cross-sectional survey was carried out of undergraduate university students in 19 public and private sector universities in Pakistan during June-August 2022. A nine-factor measurement model was tested using confirmatory factor analysis (CFA), and structural equation modeling (SEM) based on the 56 valid items obtained from three different validated scales, such as the family affluence scale (FAS-II), the multidimensional scale of perceived social support (MSPSS), and the European Health Literacy Questionnaire (the HLS-EU-Q). (3) Results: The data were collected from 1590 participants with a mean age of 21.16 (±2.027) years. The model fit indices indicate that the model partially fitted the data: χ2 = 4.435, df = 1448, p = 0.000, RMSEA = 0.048, TLI = 0.906, CFI = 0.912, IFI = 0.912, GFI = 0.872, NFI = 0.889, RFI = 0.882, PGFI = 0.791. The structural equation model showed acceptable goodness of fit indices, indicating a significant direct influence of social and family support on healthcare and disease prevention. (4) Conclusions: Social and family support are the most influential factors, with regard to HL dimensions, in improving healthcare, disease prevention, and health promotion in low-income settings and among non-English-speaking communities.

Digital Twins: From Personalised Medicine to Precision Public Health.

A digital twin is a virtual model of a physical entity, with dynamic, bi-directional links between the physical entity and its corresponding twin in the digital domain. Digital twins are increasingly used today in different industry sectors. Applied to medicine and public health, digital twin technology can drive a much-needed radical transformation of traditional electronic health/medical records (focusing on individuals) and their aggregates (covering populations) to make them ready for a new era of precision (and accuracy) medicine and public health. Digital twins enable learning and discovering new knowledge, new hypothesis generation and testing, and in silico experiments and comparisons. They are poised to play a key role in formulating highly personalised treatments and interventions in the future. This paper provides an overview of the technology's history and main concepts. A number of application examples of digital twins for personalised medicine, public health, and smart healthy cities are presented, followed by a brief discussion of the key technical and other challenges involved in such applications, including ethical issues that arise when digital twins are applied to model humans.

COVID-19 Misinformation Online and Health Literacy: A Brief Overview.

Low digital health literacy affects large percentages of populations around the world and is a direct contributor to the spread of COVID-19-related online misinformation (together with bots). The ease and 'viral' nature of social media sharing further complicate the situation. This paper provides a quick overview of the magnitude of the problem of COVID-19 misinformation on social media, its devastating effects, and its intricate relation to digital health literacy. The main strategies, methods and services that can be used to detect and prevent the spread of COVID-19 misinformation, including machine learning-based approaches, health literacy guidelines, checklists, mythbusters and fact-checkers, are then briefly reviewed. Given the complexity of the COVID-19 infodemic, it is very unlikely that any of these approaches or tools will be fully effective alone in stopping the spread of COVID-19 misinformation. Instead, a mixed, synergistic approach, combining the best of these strategies, methods, and services together, is highly recommended in tackling online health misinformation, and mitigating its negative effects in COVID-19 and future pandemics. Furthermore, techniques and tools should ideally focus on evaluating both the message (information content) and the messenger (information author/source) and not just rely on assessing the latter as a quick and easy proxy for the trustworthiness and truthfulness of the former. Surveying and improving population digital health literacy levels are also essential for future infodemic preparedness.

Smart city lifestyle sensing, big data, geo-analytics and intelligence for smarter public health decision-making in overweight, obesity and type 2 diabetes prevention: the research we should be doing.

The public health burden caused by overweight, obesity (OO) and type-2 diabetes (T2D) is very significant and continues to rise worldwide. The causation of OO and T2D is complex and highly multifactorial rather than a mere energy intake (food) and expenditure (exercise) imbalance. But previous research into food and physical activity (PA) neighbourhood environments has mainly focused on associating body mass index (BMI) with proximity to stores selling fresh fruits and vegetables or fast food restaurants and takeaways, or with neighbourhood walkability factors and access to green spaces or public gym facilities, making largely naive, crude and inconsistent assumptions and conclusions that are far from the spirit of 'precision and accuracy public health'. Different people and population groups respond differently to the same food and PA environments, due to a myriad of unique individual and population group factors (genetic/epigenetic, metabolic, dietary and lifestyle habits, health literacy profiles, screen viewing times, stress levels, sleep patterns, environmental air and noise pollution levels, etc.) and their complex interplays with each other and with local food and PA settings. Furthermore, the same food store or fast food outlet can often sell or serve both healthy and non-healthy options/portions, so a simple binary classification into 'good' or 'bad' store/outlet should be avoided. Moreover, appropriate physical exercise, whilst essential for good health and disease prevention, is not very effective for weight maintenance or loss (especially when solely relied upon), and cannot offset the effects of a bad diet. The research we should be doing in the third decade of the twenty-first century should use a systems thinking approach, helped by recent advances in sensors, big data and related technologies, to investigate and consider all these factors in our quest to design better targeted and more effective public health interventions for OO and T2D control and prevention.

Opportunistic atrial fibrillation screening and detection in "self-service health check-up stations": a brief overview of current technology potential and possibilities.

Up to a fifth of patients who suffer a stroke had undiagnosed atrial fibrillation (AF). About 30% of AF patients are asymptomatic and remain undiagnosed, so there are no obvious (to the patient) forewarnings. Opportunistic screening for AF applied to the above clinical situation can save lives, since the strokes that occur as a result of AF are often large, severely debilitating or fatal. Today, anyone can buy a good, FDA-approved mobile electrocardiogram (ECG) device/smartwatch for AF detection on Amazon for €100-400, but not very many asymptomatic AF patients, particularly older patients, will do so on their own. In this article, we introduce the concept and potential benefits of opportunistic AF screening and detection in a community setting using the latest generation of affordable digital ECG capture and interpretation solutions integrated into easy-to-use "self-service health check-up stations" installed in public spaces, such as supermarkets and pharmacies. A comprehensive trial of the proposed self-service health check-up stations for AF screening is needed to produce more evidence to convince decision makers to fully buy into the idea of a nation-wide screening programme using these kiosks.

Mobile physical activity planning and tracking: a brief overview of current options and desiderata for future solutions.

Consistent and enjoyable physical activity (PA) can be a crucial component to improving or maintaining one's overall health status. Using advanced features on smartphones (GPS, Bluetooth, motion sensing, etc.) coupled with an app or game that is able to assist mobile users to not only track location, but also to interact socially with others based in real-life (IRL), virtual reality (VR), or alternate-reality (ARG), has the potential to give health experts better tools to encourage higher compliance to protocols, rehabilitation, behaviour change and health outcomes. This paper outlines the available mHealth apps that capitalize on pervasive smartphone features coupled with sensors, and suggests which features might impact future PA patterns. The authors argue that the ultimate mobile PA planning and tracking app/platform will be the one capable of supporting both precision and accuracy health (offering truly individualized PA advice and coaching while preserving user privacy) and precision and accuracy public health (providing public health decision makers with community-level PA indicators obtained from app data aggregates of user populations).

Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics.

In December 2019, a new virus (initially called 'Novel Coronavirus 2019-nCoV' and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China's massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics.

An overview of GeoAI applications in health and healthcare.

The moulding together of artificial intelligence (AI) and the geographic/geographic information systems (GIS) dimension creates GeoAI. There is an emerging role for GeoAI in health and healthcare, as location is an integral part of both population and individual health. This article provides an overview of GeoAI technologies (methods, tools and software), and their current and potential applications in several disciplines within public health, precision medicine, and Internet of Things-powered smart healthy cities. The potential challenges currently facing GeoAI research and applications in health and healthcare are also briefly discussed.

Effective uses of social media in public health and medicine: a systematic review of systematic reviews.

INTRODUCTION: Research examining the effective uses of social media (SM) in public health and medicine, especially in the form of systematic reviews (SRs), has grown considerably in the past decade. To our knowledge, no comprehensive synthesis of this literature has been conducted to date. AIMS AND METHODS: To conduct a systematic review of systematic reviews of the benefits and harms ("effects") of SM tools and platforms (such as Twitter and Facebook) in public health and medicine. To perform a synthesis of this literature and create a 'living systematic review'. RESULTS: Forty-two (42) high-quality SRs were examined. Overall, evidence of SM's effectiveness in public health and medicine was judged to be minimal. However, qualitative benefits for patients are seen in improved psychosocial support and psychological functioning. Health professionals benefited from better peer-to-peer communication and lifelong learning. Harms on all groups include the impact of SM on mental health, privacy, confidentiality and information reliability. CONCLUSIONS: A range of negatives and positives of SM in public health and medicine are seen in the SR literature but definitive conclusions cannot be made at this time. Clearly better research designs are needed to measure the effectiveness of social technologies. For ongoing updates, see the wiki "Effective uses of social media in health: a living systematic review of systematic reviews". http://hlwiki.slais.ubc.ca/index.php/Effective_uses_of_social_media_in_healthcare:_a_living_systematic_review_of_reviews.

Geospatial blockchain: promises, challenges, and scenarios in health and healthcare.

A PubMed query run in June 2018 using the keyword 'blockchain' retrieved 40 indexed papers, a reflection of the growing interest in blockchain among the medical and healthcare research and practice communities. Blockchain's foundations of decentralisation, cryptographic security and immutability make it a strong contender in reshaping the healthcare landscape worldwide. Blockchain solutions are currently being explored for: (1) securing patient and provider identities; (2) managing pharmaceutical and medical device supply chains; (3) clinical research and data monetisation; (4) medical fraud detection; (5) public health surveillance; (6) enabling truly public and open geo-tagged data; (7) powering many Internet of Things-connected autonomous devices, wearables, drones and vehicles, via the distributed peer-to-peer apps they run, to deliver the full vision of smart healthy cities and regions; and (8) blockchain-enabled augmented reality in crisis mapping and recovery scenarios, including mechanisms for validating, crediting and rewarding crowdsourced geo-tagged data, among other emerging use cases. Geospatially-enabled blockchain solutions exist today that use a crypto-spatial coordinate system to add an immutable spatial context that regular blockchains lack. These geospatial blockchains do not just record an entry's specific time, but also require and validate its associated proof of location, allowing accurate spatiotemporal mapping of physical world events. Blockchain and distributed ledger technology face similar challenges as any other technology threatening to disintermediate legacy processes and commercial interests, namely the challenges of blockchain interoperability, security and privacy, as well as the need to find suitable and sustainable business models of implementation. Nevertheless, we expect blockchain technologies to get increasingly powerful and robust, as they become coupled with artificial intelligence (AI) in various real-word healthcare solutions involving AI-mediated data exchange on blockchains.

Head-Mounted Virtual Reality and Mental Health: Critical Review of Current Research.

BACKGROUND: eHealth interventions are becoming increasingly used in public health, with virtual reality (VR) being one of the most exciting recent developments. VR consists of a three-dimensional, computer-generated environment viewed through a head-mounted display. This medium has provided new possibilities to adapt problematic behaviors that affect mental health. VR is no longer unaffordable for individuals, and with mobile phone technology being able to track movements and project images through mobile head-mounted devices, VR is now a mobile tool that can be used at work, home, or on the move. OBJECTIVE: In line with recent advances in technology, in this review, we aimed to critically assess the current state of research surrounding mental health. METHODS: We compiled a table of 82 studies that made use of head-mounted devices in their interventions. RESULTS: Our review demonstrated that VR is effective in provoking realistic reactions to feared stimuli, particularly for anxiety; moreover, it proved that the immersive nature of VR is an ideal fit for the management of pain. However, the lack of studies surrounding depression and stress highlight the literature gaps that still exist. CONCLUSIONS: Virtual environments that promote positive stimuli combined with health knowledge could prove to be a valuable tool for public health and mental health. The current state of research highlights the importance of the nature and content of VR interventions for improved mental health. While future research should look to incorporate more mobile forms of VR, a more rigorous reporting of VR and computer hardware and software may help us understand the relationship (if any) between increased specifications and the efficacy of treatment.

Measuring management's perspective of data quality in Pakistan's Tuberculosis control programme: a test-based approach to identify data quality dimensions.

BACKGROUND: Data quality is core theme of programme's performance assessment and many organizations do not have any data quality improvement strategy, wherein data quality dimensions and data quality assessment framework are important constituents. As there is limited published research about the data quality specifics that are relevant to the context of Pakistan's Tuberculosis control programme, this study aims at identifying the applicable data quality dimensions by using the 'fitness-for-purpose' perspective. RESULTS: Forty-two respondents pooled a total of 473 years of professional experience, out of which 223 years (47%) were in TB control related programmes. Based on the responses against 11 practical cases, adopted from the routine recording and reporting system of Pakistan's TB control programme (real identities of patient were masked), completeness, accuracy, consistency, vagueness, uniqueness and timeliness are the applicable data quality dimensions relevant to the programme's context, i.e. work settings and field of practice. CONCLUSION: Based on a 'fitness-for-purpose' approach to data quality, this study used a test-based approach to measure management's perspective and identified data quality dimensions pertinent to the programme and country specific requirements. Implementation of a data quality improvement strategy and achieving enhanced data quality would greatly help organizations in promoting data use for informed decision making.

From urban planning and emergency training to Pokémon Go: applications of virtual reality GIS (VRGIS) and augmented reality GIS (ARGIS) in personal, public and environmental health.

The latest generation of virtual and mixed reality hardware has rekindled interest in virtual reality GIS (VRGIS) and augmented reality GIS (ARGIS) applications in health, and opened up new and exciting opportunities and possibilities for using these technologies in the personal and public health arenas. From smart urban planning and emergency training to Pokémon Go, this article offers a snapshot of some of the most remarkable VRGIS and ARGIS solutions for tackling public and environmental health problems, and bringing about safer and healthier living options to individuals and communities. The article also covers the main technical foundations and issues underpinning these solutions.