Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Healthcare, Год журнала: 2024, Номер 12(2), С. 125 - 125

Опубликована: Янв. 5, 2024

Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of improving patient outcomes and optimizing delivery. By harnessing machine learning algorithms, natural language processing, computer vision, AI enables analysis complex medical data. The integration into systems aims to support clinicians, personalize care, enhance population health, all while addressing challenges posed by rising costs limited resources. As subdivision science, focuses on development advanced algorithms capable performing tasks that were once reliant human intelligence. ultimate goal is achieve human-level performance improved efficiency accuracy problem-solving task execution, thereby reducing need for intervention. Various industries, including engineering, media/entertainment, finance, education, have already reaped significant benefits incorporating their operations. Notably, sector witnessed rapid growth utilization technology. Nevertheless, there remains untapped potential truly revolutionize industry. It important note despite concerns about job displacement, should not be viewed threat workers. Instead, are designed augment professionals, freeing up time focus more critical tasks. automating routine repetitive tasks, can alleviate burden allowing them dedicate attention care meaningful interactions. However, legal ethical must addressed when embracing technology medicine, alongside comprehensive public education ensure widespread acceptance.

Язык: Английский

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Harnessing the Power of AI: A Comprehensive Review of Its Impact and Challenges in Nursing Science and Healthcare

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 22, 2023

This comprehensive review delves into the impact and challenges of Artificial Intelligence (AI) in nursing science healthcare. AI has already demonstrated its transformative potential these fields, with applications spanning from personalized care diagnostic accuracy to predictive analytics telemedicine. However, integration complexities, including concerns related data privacy, ethical considerations, biases algorithms datasets. The future healthcare appears promising, poised advance diagnostics, treatment, practices. Nevertheless, it is crucial remember that should complement, not replace, professionals, preserving essential human element care. To maximize AI's healthcare, interdisciplinary collaboration, guidelines, protection patient rights are essential. concludes a call action, emphasizing need for ongoing research collective efforts ensure contributes improved outcomes while upholding highest standards ethics patient-centered

Язык: Английский

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Intrusion Detection in Healthcare 4.0 Internet of Things Systems via Metaheuristics Optimized Machine Learning

Sustainability, Год журнала: 2023, Номер 15(16), С. 12563 - 12563

Опубликована: Авг. 18, 2023

Rapid developments in Internet of Things (IoT) systems have led to a wide integration such into everyday life. Systems for active real-time monitoring are especially useful areas where rapid action can significant impact on outcomes as healthcare. However, major challenge persists within IoT that limit wider integration. Sustainable healthcare supported by the must provide organized population, without compromising environment. Security plays role sustainability systems, therefore detecting and taking timely is one step overcoming challenges. This work tackles security challenges head-on through use machine learning algorithms optimized via modified Firefly algorithm issues devices used Healthcare 4.0. Metaheuristic solutions contributed various they solve nondeterministic polynomial time-hard problem (NP-hard) problems realistic time with accuracy which paramount sustainable any sector Experiments synthetic dataset generated an advanced configuration tool structures performed. Also, multiple well-known models were introducing firefly metaheuristics. The best been subjected SHapley Additive exPlanations (SHAP) analysis determine factors contribute occurring issues. Conclusions from all performed testing comparisons indicate improvements formulated problem.

Язык: Английский

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Empowering Precision Medicine: The Impact of 3D Printing on Personalized Therapeutic

AAPS PharmSciTech, Год журнала: 2023, Номер 24(8)

Опубликована: Ноя. 14, 2023

Abstract This review explores recent advancements and applications of 3D printing in healthcare, with a focus on personalized medicine, tissue engineering, medical device production. It also assesses economic, environmental, ethical considerations. In our the literature, we employed comprehensive search strategy, utilizing well-known databases like PubMed Google Scholar. Our chosen keywords encompassed essential topics, including printing, nanotechnology, related areas. We first screened article titles abstracts then conducted detailed examination selected articles without imposing any date limitations. The for inclusion, comprising research studies, clinical investigations, expert opinions, underwent meticulous quality assessment. methodology ensured incorporation high-quality sources, contributing to robust exploration role realm healthcare. highlights printing's potential customized drug delivery systems, patient-specific implants, prosthetics, biofabrication organs. These innovations have significantly improved patient outcomes. Integration nanotechnology has enhanced precision biocompatibility. demonstrates cost-effectiveness sustainability through optimized material usage recycling. healthcare sector witnessed remarkable progress promoting patient-centric approach. From implants radiation shielding offers tailored solutions. Its transformative applications, coupled economic viability sustainability, revolutionize Addressing biocompatibility, standardization, concerns is responsible adoption. Graphical

Язык: Английский

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Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study

Heliyon, Год журнала: 2024, Номер 10(4), С. e25718 - e25718

Опубликована: Фев. 1, 2024

BackgroundThe healthcare landscape is rapidly evolving, with artificial intelligence (AI) emerging as a transformative force. In this context, understanding the viewpoints of nursing professionals regarding integration AI in future care crucial.AimsThis study aimed to provide insights into perceptions role shaping healthcare.MethodsA cohort 23 was recruited between April 7, 2023, and May 4, for study. Employing thematic analysis approach, qualitative data from interviews were analyzed. Verbatim transcripts underwent rigorous coding, these codes organized themes through constant comparative analysis. The refined developed grouping related codes, ensuring an authentic representation participants' viewpoints.ResultsAfter careful analysis, ten key emerged including: (I) Perceptions readiness; (II) Benefits concerns; (III) Enhanced patient outcomes; (IV) Collaboration workflow; (V) Human-tech balance: (VI) Training skill development; (VII) Ethical legal considerations; (VIII) implementation barriers; (IX) Patient-nurse relationships; (X) Future vision adaptation.ConclusionThis provides valuable professionals' perspectives on care. It highlights their enthusiasm AI's potential benefits while emphasizing importance ethical compassionate practice. findings underscore need comprehensive training programs equip skills necessary successful integration. Ultimately, research contributes ongoing discourse nursing, paving way where innovative technologies complement enhance delivery patient-centered

Язык: Английский

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Advancing Clinical Decision Support: The Role of Artificial Intelligence Across Six Domains

Computer Methods and Programs in Biomedicine Update, Год журнала: 2024, Номер 5, С. 100142 - 100142

Опубликована: Янв. 1, 2024

Язык: Английский

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Effect of digital based nursing intervention on knowledge of self-care behaviors and self-efficacy of adult clients with diabetes

BMC Nursing, Год журнала: 2024, Номер 23(1)

Опубликована: Фев. 20, 2024

Abstract Background In recent years, there has been growing interest in the use of Digital Based Nursing Intervention to support diabetes management. This study aimed evaluate effect digital based nursing intervention on knowledge self-care behaviors and self-efficacy clients with diabetes. Methods Employing a quasi-experimental design, sample 120 adult participants diagnosed type 2 diabetes, aged more than 18 years focus older adults was drawn from outpatient clinics at Cairo University Hospital. The approved registered by ethical committee faculty IRB number: RHDIRB2019041701. group ( n = 60) received digital-based intervention, while control standard care. Data were collected using adopted standardized tools including Diabetes Knowledge Test, Self-Efficacy Scale, Summary Self-Care Activities. Demographic characteristics analyzed, pre- post-intervention scores compared paired t-tests statistical methods. Results resulted significant enhancements levels. Moreover, demonstrated marked improvements various encompassing diet, exercise, medication adherence, blood glucose testing, foot While also exhibited some progress, effects less pronounced. Regression analyses highlighted age as consistent factor associated knowledge, self-efficacy, specific behaviors. Conclusion underscores potential tailored interventions complement traditional care approaches, empowering patients actively engage self-management. findings suggest that hold promise for enhancing patient confidence, proactive health Nevertheless, limitations, relatively short duration single clinic, warrant consideration. Future research should address these limitations bolster validity applicability study’s conclusions.

Язык: Английский

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Envisioning the Future of ChatGPT in Healthcare: Insights and Recommendations from a Systematic Identification of Influential Research and a Call for Papers

Jordan Medical Journal, Год журнала: 2024, Номер 58(1)

Опубликована: Фев. 19, 2024

Background and Aims: ChatGPT represents the most popular widely used generative artificial intelligence (AI) model that received significant attention in healthcare research. The aim of current study was to assess future trajectory needed research this domain based on recommendations top influential published records. Materials Methods: A systematic search conducted Scopus, Web Science, Google Scholar (27–30 November 2023) identify ten ChatGPT-related records across three databases. Classification as “top” denoting high influence field citation counts. Results: total 22 unique from 17 different journals representing 14 publishers were identified publications subject. Based records’ recommendations, following themes appeared important areas consider healthcare: improving education, improved efficiency clinical processes (e.g., documentation), addressing ethical concerns patient privacy consent), supporting tasks data analysis, manuscript preparation), mitigating output biases, education engagement, developing standardized assessment protocols for utility healthcare. Conclusions: review highlighted key be prioritized healthcare. Interdisciplinary collaborations standardizing methodologies are synthesize robust evidence these studies. promising potential healthcare, JMJ launched a call papers special issue entitled “Evaluating Generative AI-Based Models Healthcare”.

Язык: Английский

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The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency

Health Science Reports, Год журнала: 2025, Номер 8(1)

Опубликована: Янв. 1, 2025

Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims describe AI including important technologies like robotics, machine learning (ML), deep (DL), natural language processing (NLP), investigate how these are used patient interaction, predictive analytics, remote monitoring. goal of this review present thorough analysis AI's effects on healthcare while providing stakeholders with road map for navigating changing environment. This analyzes the impact using data from Web Science (2014-2024), focusing keywords AI, ML, applications. It examines uses by synthesizing recent literature real-world case studies, such as Google Health IBM Watson Health, highlighting technologies, their useful applications, difficulties putting them into practice, problems security resource limitations. also discusses new developments they can affect society. findings demonstrate enhancing skills medical professionals, diagnosis, opening door more individualized treatment plans, reflected steady rise AI-related publications 158 articles (3.54%) 2014 731 (16.33%) 2024. Core applications monitoring analytics improve effectiveness involvement. However, there major obstacles mainstream implementation issues budget constraints. Healthcare may be transformed but its successful use requires ethical responsible use. To meet demands sector guarantee application evaluation highlights necessity ongoing research, instruction, multidisciplinary cooperation. In future, integrating responsibly will essential optimizing advantages reducing related dangers.

Язык: Английский

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Prediction and detection of terminal diseases using Internet of Medical Things: A review

Computers in Biology and Medicine, Год журнала: 2025, Номер 188, С. 109835 - 109835

Опубликована: Фев. 24, 2025

Язык: Английский

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