AI-DRIVEN ENVIRONMENTAL HEALTH DISEASE MODELING: A REVIEW OF TECHNIQUES AND THEIR IMPACT ON PUBLIC HEALTH IN THE USA AND AFRICAN CONTEXTS

International Medical Science Research Journal, Год журнала: 2024, Номер 4(1), С. 51 - 73

Опубликована: Янв. 23, 2024

This scholarly paper embarks on an exploratory journey into the realm of AI-driven environmental health disease modeling, with a keen focus its implications in diverse healthcare landscapes USA and Africa. The study's background delves historical evolution modeling techniques, emphasizing revolutionary role AI modern public strategies. It meticulously examines comparative effectiveness models these distinct regions, addressing challenges opportunities inherent models. Aiming to unravel multifaceted impact prediction policy, navigates through various thematic corridors. critically analyzes significance data sources quality, ethical considerations integration policies. scope encompasses comprehensive review AI's efficacy predicting diseases, enhancing surveillance systems, geographic socioeconomic variations affecting model accuracy. main findings reveal that models, while effective surveillance, encounter related integrity complexities. study concludes necessitates balanced approach, advocating for policies support development context-specific address concerns. Recommendations include fostering interdisciplinary collaboration continuous evaluation align them evolving needs standards. serves as beacon understanding transformative potential offering insights are crucial shaping future strategies interventions. Keywords: Healthcare, Disease Modeling, Public Health Policy, Data Quality, Ethical Considerations, Geographic Variations.

Язык: Английский

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Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study

Journal of Medical Internet Research, Год журнала: 2024, Номер 26, С. e49139 - e49139

Опубликована: Янв. 19, 2024

Background Previous work suggests that Google searches could be useful in identifying conjunctivitis epidemics. Content-based assessment of social media content may provide additional value serving as early indicators and other systemic infectious diseases. Objective We investigated whether large language models, specifically GPT-3.5 GPT-4 (OpenAI), can probabilistic assessments posts about indicate a regional outbreak. Methods A total 12,194 conjunctivitis-related tweets were obtained using targeted Boolean search multiple languages from India, Guam (United States), Martinique (France), the Philippines, American Samoa Fiji, Costa Rica, Haiti, Bahamas, covering time frame January 1, 2012, to March 13, 2023. By providing these via prompts GPT-4, we validated by 2 human raters. then calculated Pearson correlations series with tweet volume occurrence known outbreaks 9 locations, bootstrap used compute CIs. Results Probabilistic derived showed 0.60 (95% CI 0.47-0.70) 0.53 0.40-0.65) raters, higher results for GPT-4. The weekly averages probabilities substantial 44% (4/9) countries, ranging 0.10 0.0-0.29) 0.39-0.89), larger More modest found correlation epidemics, only (0.40, 95% 0.16-0.81). Conclusions These findings suggest GPT prompting efficiently assess possible disease degree accuracy comparable humans. Furthermore, automated analysis is related some locations actual Future improve sensitivity specificity methods outbreak detection.

Язык: Английский

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Transformers and large language models in healthcare: A review

Artificial Intelligence in Medicine, Год журнала: 2024, Номер 154, С. 102900 - 102900

Опубликована: Июнь 5, 2024

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption Transformers neural network architecture is rapidly changing many applications. Transformer a type deep learning initially developed to solve general-purpose Natural Language Processing (NLP) tasks and has subsequently been adapted in fields, healthcare. In this survey paper, we provide an overview how adopted analyze forms healthcare data, clinical NLP, medical imaging, structured Electronic Health Records (EHR), social media, bio-physiological signals, biomolecular sequences. Furthermore, which have also include articles that used transformer for generating surgical instructions predicting adverse outcomes after surgeries under umbrella critical care. Under diverse settings, these models diagnosis, report generation, data reconstruction, drug/protein synthesis. Finally, discuss benefits limitations using transformers examine issues such as computational cost, model interpretability, fairness, alignment with human values, ethical implications, environmental impact.

Язык: Английский

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Racial and Ethnic Digital Divides in Posting COVID-19 Content on Social Media Among US Adults: Secondary Survey Analysis

Journal of Medical Internet Research, Год журнала: 2020, Номер 22(7), С. e20472 - e20472

Опубликована: Июнь 22, 2020

Public health surveillance experts are leveraging user-generated content on social media to track the spread and effects of COVID-19. However, racial ethnic digital divides, which disparities among people who have internet access post media, can bias inferences. This is particularly problematic in context COVID-19 pandemic because due structural inequalities, members minority groups disproportionately vulnerable contracting virus deleterious economic from mitigation efforts. Further, important demographic intersections with race ethnicity, such as gender age, rarely investigated work characterizing users; however, they reflect additional axes inequality shaping differential exposure its effects.

Язык: Английский

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Digital Contact Tracing for Pandemic Response

Johns Hopkins University Press eBooks, Год журнала: 2020, Номер unknown

Опубликована: Янв. 1, 2020

Digital technologies are being developed and promoted to support the public health response COVID-19 pandemic, with discussion implementation planning in United States by localities, states, institutions, employers.Key decision makers stakeholders-including government officials, institutional leaders, employers, digital technology developers, public-require clear well-supported guidance inform deployment use of these as well data they collect, store, share.While technology-based approaches currently unable provide solutions on their own, experiences other countries indicate that could be used successfully conjunction traditional novel methods.This report reflects a rapid research expert consensus group effort led Berman Institute Bioethics Center for Health Security at Johns Hopkins University.It draws experts from both inside outside bioethics, security, health, development, engineering, policy, law.The highlights issues must addressed provides recommendations part contact tracing.The analysis offered here is focused answering following questions:• Can tracing (DCTT) effective responses if so, what degree, which specific types functions, confidence, requirements?• How can serve interests while respecting individual collective interests, such ensuring equitable distribution benefits burdens limiting infringement privacy civil liberties?x Preface• What ethical, legal, governance guardrails place around else needed?• additional required ensure goals using achievable ways ethically legally sound?To answer questions, examines some core aspects applied tracing, focusing on:• value basic methods surveillance tracing,• candidate technological products enhance how work, comparative health,• considerations, relate relevant features solutions, and• needed move forward responsibly surveillance, acknowledging gaps our current understanding.The project involved in-depth dedicated team faculty, postdoctoral fellows, staff working over course only few weeks but great intensity, drafting collaboration 26 total contributors writing, commenting, revising through multiple drafts, penultimate draft "pressure-tested" review virtual workshop invited stakeholders held May 13, 2020, final version completed 21, 2020.The builds excellent work others parts this territory, areas have not been sufficiently addressed.The goal offer comprehensive advance during pandemic.Given rapidly evolving territory into DCTT introduced, will, necessity, something living document, updated often information dictates order continue leading-edge guidance.Versions will noted print editions.xi Efforts like require teams even small armies carried out successfully, was no exception, except it many fewer people more hours than reasonably expected them.From initial kernel an idea publication book form, took just month total.That seems impossible, I know accurate, speaks incredible commitment, hard skills, analytic acumen colleagues Hopkins-the deservedly listed lead authors report.None would possible without support-moral financial-and encouragement University President Ronald J. Daniels, who first suggest me taking topic.He provided

Язык: Английский

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