Generative-AI-Driven Human Digital Twin in IoT Healthcare: A Comprehensive Survey

IEEE Internet of Things Journal, Journal Year: 2024, Volume and Issue: 11(21), P. 34749 - 34773

Published: July 24, 2024

The Internet of Things (IoT) can significantly enhance the quality human life, specifically in healthcare, attracting extensive attentions to IoT healthcare services. Meanwhile, digital twin (HDT) is proposed as an innovative paradigm that comprehensively characterize replication individual body world and reflect its physical status real time. Naturally, HDT envisioned empower beyond application monitoring by acting a versatile vivid testbed, simulating outcomes guiding practical treatments. However, successfully establishing requires high-fidelity virtual modeling strong information interactions but possibly with scarce, biased, noisy data. Fortunately, recent popular technology called generative artificial intelligence (GAI) may be promising solution because it leverage advanced AI algorithms automatically create, manipulate, modify valuable while diverse This survey particularly focuses on implementation GAI-driven healthcare. We start introducing background potential HDT. Then, we delve into fundamental techniques present overall framework After that, explore realization detail, including GAI-enabled data acquisition, communication, management, modeling, analysis. Besides, discuss typical applications revolutionized HDT, namely, personalized health diagnosis, prescription, rehabilitation. Finally, conclude this highlighting some future research directions.

Language: Английский

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Unleashing the Power of Generative AI in Agriculture 4.0 for Smart and Sustainable Farming

Cognitive Computation, Journal Year: 2025, Volume and Issue: 17(1)

Published: Feb. 1, 2025

Language: Английский

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Multimodal Integration in Large Language Models: A Case Study with Mistral LLM

Published: April 22, 2024

This work presents significant advancements in the multimodal capabilities of Mistral 8x7B model, a large language model designed with eight experts seven billion parameters each. We introduce comprehensive modifications to its architecture, data fusion techniques, and training procedures, aimed at improving integration processing text, image, audio data. Our experimental results demonstrate that these enhancements lead superior performance across multiple modalities when compared existing benchmarks. The improved showcases enhanced accuracy, F1 scores, index, confirming ability offer more coherent contextually appropriate outputs. research not only sets new benchmarks for models but also opens up further avenues applying such real-world, diverse, dynamic environments.

Language: Английский

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Generative Artificial Intelligence Biases, Limitations and Risks in Nuclear Medicine: An Argument for Appropriate Use Framework and Recommendations

Seminars in Nuclear Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: June 1, 2024

Generative artificial intelligence (AI) algorithms for both text-to-text and text-to-image applications have seen rapid widespread adoption in the general medical communities. While limitations of generative AI been widely reported, there remain valuable patient professional Here, biases are explored using purported imaging as case examples. A direct comparison capabilities four common is reported recommendations most appropriate use, DALL-E 3, justified. The risks use outlined, guidelines framed nuclear medicine. generation includes inherent biases, particularly gender ethnicity, that could misrepresent assimilation tools into education, image interpretation, health promotion marketing medicine propagating errors amplification biases. Mitigation strategies should reside inside criteria minimum standards quality professionalism application

Language: Английский

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Harnessing EHR data for health research

Nature Medicine, Journal Year: 2024, Volume and Issue: 30(7), P. 1847 - 1855

Published: July 1, 2024

Language: Английский

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Innovations in Medicine: Exploring ChatGPT’s Impact on Rare Disorder Management

Genes, Journal Year: 2024, Volume and Issue: 15(4), P. 421 - 421

Published: March 28, 2024

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era innovation and efficiency. Among AI programs designed for general use, ChatGPT holds prominent position, using an innovative language model developed by OpenAI. Thanks to use deep learning techniques, stands out as exceptionally viable tool, renowned generating human-like responses queries. Various medical specialties, including rheumatology, oncology, psychiatry, internal ophthalmology, have been explored integration, with pilot studies trials revealing each field’s potential benefits challenges. However, genetics genetic counseling, well that rare disorders, represents area suitable exploration, its complex datasets need personalized patient care. In this review, we synthesize wide range applications in field, highlighting limitations. We pay special attention aiming shed light on future roles AI-driven chatbots healthcare. Our goal pave way healthcare system more knowledgeable, efficient, centered around needs.

Language: Английский

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Augmenting Community Nursing Practice With Generative AI: A Formative Study of Diagnostic Synergies Using Simulation-Based Clinical Cases

Journal of Primary Care & Community Health, Journal Year: 2025, Volume and Issue: 16

Published: March 1, 2025

Objective: To compare the diagnostic accuracy and clinical decision-making of experienced community nurses versus state-of-the-art generative AI (GenAI) systems for simulated patient case scenarios. Methods: In months 5 to 6/2024, 114 Israeli completed a questionnaire including 4 medical studies. Responses were also collected from 3 GenAI models (ChatGPT-4, Claude 3.0, Gemini 1.5), analyzed both without word limits with 10-word constraint. scored on accuracy, speed, comprehensiveness. Results: Nurses higher average compared shortened responses. responses faster but more verbose, contained unnecessary information. (full version) achieved highest among models. Conclusions: While shows potential support aspects nursing practice, human clinicians currently exhibit advantages in holistic reasoning abilities, skill requiring experience, contextual knowledge, ability bring concise practical Further research is needed before can adequately substitute expertise.

Language: Английский

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Evaluating ChatGPT-4’s Accuracy in Identifying Final Diagnoses Within Differential Diagnoses Compared With Those of Physicians: Experimental Study for Diagnostic Cases

JMIR Formative Research, Journal Year: 2024, Volume and Issue: 8, P. e59267 - e59267

Published: May 4, 2024

Background The potential of artificial intelligence (AI) chatbots, particularly ChatGPT with GPT-4 (OpenAI), in assisting medical diagnosis is an emerging research area. However, it not yet clear how well AI chatbots can evaluate whether the final included differential lists. Objective This study aims to assess capability identifying from differential-diagnosis lists and compare its performance that physicians for case report series. Methods We used a database reports American Journal Case Reports, corresponding diagnoses. These were generated by 3 systems: GPT-4, Google Bard (currently Gemini), Large Language Models Meta 2 (LLaMA2). primary outcome was focused on GPT-4’s evaluations identified within these None AIs received additional training or reinforcement. For comparison, independent also evaluated lists, any inconsistencies resolved another physician. Results total 1176 392 descriptions. concurred those 966 out (82.1%). Cohen κ coefficient 0.63 (95% CI 0.56-0.69), indicating fair good agreement between physicians’ evaluations. Conclusions demonstrated comparable Its ability diagnoses suggests aid clinical decision-making support through diagnostic feedback. While showed evaluation, application real-world scenarios further validation diverse environments are essential fully understand utility process.

Language: Английский

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Research design and writing of scholarly articles: new artificial intelligence tools available for researchers

Endocrine, Journal Year: 2024, Volume and Issue: 85(3), P. 1104 - 1116

Published: July 31, 2024

Language: Английский

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Applying analytics to sociodemographic disparities in mental health

Nature Mental Health, Journal Year: 2025, Volume and Issue: 3(1), P. 124 - 138

Published: Jan. 8, 2025

Language: Английский

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