Overcoming LLM Challenges using RAG-Driven Precision in Coffee Leaf Disease Remediation

Опубликована: Апрель 22, 2024

This research introduces an innovative AI-driven precision agriculture system, leveraging YOLOv8 for disease identification and Retrieval Augmented Generation (RAG) context-aware diagnosis. Focused on addressing the challenges of diseases affecting coffee production sector in Karnataka, The system integrates sophisticated object detection techniques with language models to address inherent constraints associated Large Language Models (LLMs). Our methodology not only tackles issue hallucinations LLMs, but also dynamic remediation strategies. Real-time monitoring, collaborative dataset expansion, organizational involvement ensure system's adaptability diverse agricultural settings. effect suggested extends beyond automation, aiming secure food supplies, protect livelihoods, promote eco-friendly farming practices. By facilitating precise identification, contributes sustainable environmentally conscious agriculture, reducing reliance pesticides. Looking future, project envisions continuous development RAG-integrated systems, emphasizing scalability, reliability, usability. strives be a beacon positive change aligning global efforts toward technologically enhanced production.

Язык: Английский

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Zero-shot learning to extract assessment criteria and medical services from the preventive healthcare guidelines using large language models

Journal of the American Medical Informatics Association, Год журнала: 2024, Номер 31(8), С. 1743 - 1753

Опубликована: Июнь 20, 2024

Abstract Objectives The integration of these preventive guidelines with Electronic Health Records (EHRs) systems, coupled the generation personalized care recommendations, holds significant potential for improving healthcare outcomes. Our study investigates feasibility using Large Language Models (LLMs) to automate assessment criteria and risk factors from future analysis against medical records in EHR. Materials Methods We annotated criteria, factors, services described adult published by United States Preventive Services Taskforce evaluated 3 state-of-the-art LLMs on extracting information categories automatically. Results included 24 this study. can extraction all 9 guidelines. All perform well regarding demographic or factors. Some better social determinants health, family history, counseling than others. Discussion While demonstrate capability handle lengthy guidelines, several challenges persist, including constraints related maximum length input tokens tendency generate content rather adhering strictly original input. Moreover, utilization real-world clinical settings necessitates careful ethical consideration. It is imperative that professionals meticulously validate extracted mitigate biases, ensure completeness, maintain accuracy. Conclusion developed a data structure store make it publicly available. Employing extract paves way into

Язык: Английский

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Generative AI Decision-Making Attributes in Complex Health Services: A Rapid Review

Cureus, Год журнала: 2025, Номер unknown

Опубликована: Янв. 30, 2025

The advent of Generative Artificial Intelligence (Generative AI or GAI) marks a significant inflection point in development. Long viewed as the epitome reasoning and logic, incorporates programming rules that are normative. However, it also has descriptive component based on its programmers' subjective preferences any discrepancies underlying data. generates both truth falsehood, supports ethical unethical decisions, is neither transparent nor accountable. These factors pose clear risks to optimal decision-making complex health services such policy regulation. It important examine how makes decisions from rational, normative perspective view ensure an approach design, engineering, use. objective provide rapid review identifies maps attributes reported literature influence services. This provides clear, reproducible methodology accordance with recognised framework Preferred Reporting Items for Systematic reviews Meta-Analyses (PRISMA) 2020 standards adapted review. Inclusion exclusion criteria were developed, database search was undertaken within four systems: ProQuest, Scopus, Web Science, Google Scholar. results include articles published 2023 early 2024. A total 1,550 identified. After removing duplicates, 1,532 remained. Of these, 1,511 excluded selection 21 selected analysis. Learning, understanding, bias most frequently mentioned attributes. brings promise advanced automation, but carries risk. Learning pattern recognition helpful, lack moral compass, empathy, consideration privacy, propensity hallucination detrimental good decision-making. suggest there is, perhaps, more work be done before can applied

Язык: Английский

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Navigating the Medical Landscape: A Review of Chatbots for Biomarker Extraction from Diverse Medical Reports

International Journal For Multidisciplinary Research, Год журнала: 2024, Номер 6(1)

Опубликована: Фев. 6, 2024

This research investigates the potential of chatbots to revolutionize extraction biomarkers from a variety medical reports, such as pathology CT scans, and Electronic Health Record (EHR) notes. The sheds light on histories, training approaches, uses popular including ChatGPT, Google Bard, Jasper Chat through comparative examination, providing insights into their efficacy in healthcare settings. Issues with data privacy, complicated integration, ethical issues, technological constraints are explored, illuminating challenging terrain deploying for biomarker extraction. ramifications discussed comes close, focus possibility better patient outcomes, more accurate diagnosis, development tailored therapy. Future recommendations emphasize continued need algorithm optimization, innovative integration exploration, considerations.

Язык: Английский

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AI-Powered Crisis Response: Streamlining Emergency Management with LLMs

Опубликована: Май 14, 2024

Язык: Английский

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Application of Large Language Models in Medical Training Evaluation: Can ChatGPT Be a Standardized Patient? An Exploratory Study (Preprint)

Journal of Medical Internet Research, Год журнала: 2024, Номер 27, С. e59435 - e59435

Опубликована: Ноя. 11, 2024

With the increasing interest in application of large language models (LLMs) medical field, feasibility its potential use as a standardized patient assessment is rarely evaluated. Specifically, we delved into using ChatGPT, representative LLM, transforming education by serving cost-effective alternative to patients, specifically for history-taking tasks.

Язык: Английский

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4D/5D/6D Printing Technology in the Architecture, Engineering, and Construction (AEC) Industry: Applications, Challenges, and Future Advancements

SSRN Electronic Journal, Год журнала: 2023, Номер unknown

Опубликована: Янв. 1, 2023

The convergence of 4D, 5D, and 6D printing technologies with the Architecture, Engineering, Construction (AEC) sector has ushered in an era unparalleled innovation efficiency. This study delves into diverse applications, obstacles, forthcoming advancements these cutting-edge within AEC industry. 4D printing, marked by materials that can self-transform or assemble over time, revolutionized architectural design enabling dynamic structures respond to environmental stimuli. 5D seamlessly integrates cost estimation fabrication process, ensuring real-time project budgeting management. Additionally, incorporates sustainability data, providing architects engineers insights long-term impact their designs. These applications collectively enhance industry's capacity create are sustainable, cost-effective, adaptable. Despite promising challenges persist. Material constraints, scalability production, need for standardized processes present significant obstacles. Furthermore, integrating intricate data streams demands robust computational algorithms efficient management systems. Ethical concerns surrounding intellectual property, security, also require careful consideration. To surmount challenges, ongoing research focuses on advancing material science, innovative techniques, development intelligent algorithms. Collaboration among interdisciplinary teams, including architects, engineers, computer scientists, experts, is crucial unlocking full potential technologies. integration artificial intelligence machine learning holds promise streamlining optimizing usage, enhancing predictive modeling. approach paves way a more sustainable Embracing essential navigate complexities modern architecture, resilient built environment future generations.

Язык: Английский

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Healthcare Metaverse: Applications, Challenges, and Future Development

SSRN Electronic Journal, Год журнала: 2023, Номер unknown

Опубликована: Янв. 1, 2023

The incorporation of metaverse technologies into the healthcare sector has emerged as a revolutionary paradigm, creating new possibilities for patient care, medical research, and education. This paper explores varied applications, challenges, future prospects Healthcare Metaverse within different subfields, utilizing spectrum technologies. In domain facilitates remote consultations, monitoring, development personalized treatment plans. Virtual Reality (VR) Augmented (AR) provide immersive simulations, assisting patients in rehabilitation mental health interventions. Furthermore, investigates potential elevating education by enabling students practitioners to participate realistic, interactive scenarios surgical simulations. Medical research reaps benefits through collaborative platforms that transcend geographical boundaries. Researchers can engage shared virtual environments, thereby accelerating pace discovery innovation. delves application blockchain technology ensure secure transparent data sharing, which is crucial advancing knowledge. challenges implementing Metaverse, including concerns related privacy, technological interoperability, ethical considerations. It addresses these proposes strategies mitigation, underscoring significance interdisciplinary collaboration regulatory frameworks. Looking ahead, envisions evolution with integration emerging such Artificial Intelligence (AI), haptic feedback, Internet Things (IoT). These advancements hold promise improved diagnostic capabilities, approaches, enhanced outcomes. Across diverse surgery, diagnostics, health, rehabilitation, showcases its versatility. study reviews impact VR, AR, Mixed (MR) on each subfield, highlighting their unique contributions synergies. serves guiding resource professionals, researchers, policymakers navigating dynamic intersection

Язык: Английский

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ChatGPT and Health Communication

International Journal of E-Health and Medical Communications, Год журнала: 2024, Номер 15(1), С. 1 - 26

Опубликована: Июль 26, 2024

This systematic review aims to provide insight into ChatGPT's application in health communication. The review, based on seven academic databases, employed Boolean operators connect keywords, refining search results. Selection criteria and quality assessment ensured a comprehensive evaluation. Fourteen articles were included, focusing the of ChatGPT interpersonal Survey research methods mostly used, revealing four main advantages ten risks, such as providing inaccurate incomplete information. At present, is still not suitable for widespread Diverse linguistic cultural contexts, interdisciplinary collaboration, real patient experiences, integration with existing healthcare information systems, some ethical factors must be considered ensure effectively empowers

Язык: Английский

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Unveiling the Potential of Large Language Models

Advances in computational intelligence and robotics book series, Год журнала: 2024, Номер unknown, С. 389 - 414

Опубликована: Авг. 28, 2024

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are transforming industries by fostering innovation, automating tasks, enhancing creativity. By enabling personalized user interactions, sophisticated content creation, advanced data analytics, they revolutionizing such as healthcare, education, customer service. As these technologies evolve, can fundamentally change communication decision-making processes incorporate AI into everyday life. The objective of this book chapter is to examine the architecture components, features, functionality, domain-specific applications, recent advances, future developments LLMs. Ongoing research aims reduce biases, increase energy efficiency, facilitate interpretation. LLMs continue have potential transform many industries, including service, more. a result, will be essential for development AI-powered applications.

Язык: Английский

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