A Comprehensive Evaluation of AI-Assisted Diagnostic Tools in ENT Medicine: Insights and Perspectives from Healthcare Professionals

Journal of Personalized Medicine, Год журнала: 2024, Номер 14(4), С. 354 - 354

Опубликована: Март 28, 2024

The integration of Artificial Intelligence (AI) into healthcare has the potential to revolutionize medical diagnostics, particularly in specialized fields such as Ear, Nose, and Throat (ENT) medicine. However, successful adoption AI-assisted diagnostic tools ENT practice depends on understanding various factors; these include influences their effectiveness acceptance among professionals. This cross-sectional study aimed assess usability AI practice, determine clinical impact accuracy diagnostics ENT, measure trust confidence professionals tools, gauge overall satisfaction outlook future identify challenges, limitations, areas for improvement diagnostics. A structured online questionnaire was distributed 600 certified with at least one year experience field. assessed participants’ familiarity usability, impact, trust, satisfaction, identified challenges. total 458 respondents completed questionnaire, resulting a response rate 91.7%. majority reported (60.7%) perceived them generally usable clinically impactful. challenges existing systems, user-friendliness, accuracy, cost were identified. Trust levels varied participants, concerns regarding data privacy support. Geographic setting differences influenced perceptions experiences. highlights diverse experiences While there is general enthusiasm related integration, need be addressed widespread adoption. These findings provide valuable insights developers, policymakers, providers aiming enhance role practice.

Язык: Английский

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Protocol for a Realist Review of mHealth in Lung Cancer Screening: Understanding Mechanisms, Contexts, and Intervention Characteristics for Enhanced Participation

HRB Open Research, Год журнала: 2025, Номер 8, С. 12 - 12

Опубликована: Янв. 24, 2025

Introduction Lung cancer, the leading cause of cancer death worldwide, is often diagnosed at advanced stages to a poorer prognosis. Mobile health (mHealth) interventions, which are healthcare technology utilizing mobile or other wireless technology, promise enhanced early detection by optimising lung screening (LCS) implementation. However, their efficacy across various patient demographics and underlying mechanisms that influence LCS success remain unclear underexplored. Aim To explore mHealth interventions in promoting uptake, focusing on demographics, intervention characteristics, contexts influencing effectiveness. Methods This realist review will employ an iterative literature search databases such as PubMed, Scopus, Web Science, Embase. Selected studies be assessed for relevance rigour, extracting data features, outcomes. Data analysed thematically describe relationships between mechanisms, contexts, Additionally, engagement from key stakeholders, including experts patients, sought during synthesis phase. Conclusion aims offer comprehensive understanding how why can uptake effective different demographics. These findings provide insights into LCS, potentially earlier detections improved outcomes.

Язык: Английский

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Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review

Biomedicines, Год журнала: 2025, Номер 13(4), С. 776 - 776

Опубликована: Март 22, 2025

Background/Objectives: Artificial intelligence (AI) is rapidly transforming the landscape of modern medicine, offering advanced tools for diagnosing complex conditions. In realm venous pathologies such as chronic disease (CVD), reflux, and deep thrombosis (DVT), AI has shown tremendous potential to improve diagnostic accuracy, streamline workflows, enhance clinical decision-making. This study aims evaluate efficacy feasibility algorithms in diseases explore their impact on practice. Methods: paper provides a comprehensive review key studies documenting use pathology diagnostics, with different electronic databases being searched, including MEDLINE/Pub Med, Web Science, Scopus, Embase, ResearchGate, Google Scholar. Results: Out 52 reports assessed eligibility, 43 were excluded according preset criteria; therefore, findings from nine major involving more than 1000 patients analyzed. The evaluation shows that utilization diagnosis demonstrated significant improvements. Notably, have achieved an accuracy exceeding 90%, significantly reducing inter-observer variability ensuring consistent interpretation ultrasonographic images across clinicians settings. Additionally, accelerated decreasing time required image analysis by 50%. Furthermore, proven capable detecting subtle abnormalities, minor reflux or early-stage thrombi, which may be overlooked during manual evaluations. Conclusions: represents transformative innovation management diseases. By enhancing streamlining enabling personalized care, address current challenges diagnostics patient outcomes. future promising, several areas development noted, embedding directly into ultrasound devices provide instantaneous insights evaluations; combining AI-processed Doppler data other imaging modalities, computed tomography MRI, assessments; usage order predict progression tailor treatment strategies based individual profiles; constructing large-scale, multicenter datasets robustness generalizability algorithms.

Язык: Английский

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Integrated Public-Private Partnerships to Combat Tuberculosis for Improving Economic Development

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 323 - 356

Опубликована: Апрель 2, 2025

The public-private mix (PPM) involves healthcare providers and communities, addressing TB care through formal informal approaches in public private sectors. WHO emphasizes the need for PPM, particularly non-NTP sectors, to improve quality. Key issues identified include low case detection, poor treatment outcomes, delays, high patient costs. study highlights importance of notifications clinics, hospitals, pharmacies, laboratories, focusing on India. It analyzes trends enhance economic development, health align with SDG goals.

Язык: Английский

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Safeguarding Patient Confidentiality in Telemedicine: A Systematic Review of Privacy and Security Risks, and Best Practices for Data Protection

International Journal of Current Science Research and Review, Год журнала: 2024, Номер 07(06)

Опубликована: Июнь 19, 2024

The COVID-19 pandemic accelerated telemedicine adoption, showcasing its potential in improving healthcare delivery. However, privacy and security risks pose challenges, impeding widespread acceptance. aim is to investigate the integration of data analytics, analysis, cleaning telemedicine, focusing on patient security, with goal proposing strategies mitigate uphold confidentiality. Utilizing a qualitative approach, challenges were investigated. Multiple databases, including PubMed, Embase, Cochrane Library, searched from 2018-2023. Inclusion criteria involved English-language, peer-reviewed empirical studies security. Out 770 unique records screened, eight included. Full-text review risk bias assessment conducted using CASP tool. Privacy technology hurdles for providers, trust, professional training, physical disparities among special populations identified. Environmental, technological, operational factors contribute telehealth. Technology like restricted access telehealth tools poor internet hinder adoption. Data analytics facilitates transformation, addressing while optimizing outcomes through advanced techniques structured lifecycles. shows promise transformation by providing insights into behavior policy impacts, ensuring Addressing barriers, pandemic, requires infrastructure enhancements global research efforts inclusive ecosystems.

Язык: Английский

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New paradigms to break barriers in early cancer detection for improved prognosis and treatment outcomes

The Journal of Gene Medicine, Год журнала: 2024, Номер 26(8)

Опубликована: Авг. 1, 2024

The uncontrolled growth and spread of cancerous cells beyond their usual boundaries into surrounding tissues characterizes cancer. In developed countries, cancer is the leading cause death, while in underdeveloped nations, it ranks second. Using existing diagnostic tools has increased early detection rates, which crucial for effective treatment. recent decades, there been significant progress cancer-specific survival rates owing to advances ability accurately identify precursor lesions a aspect screening programs, as enables treatment initiation, lower long-term incidence invasive improved overall prognosis. However, these methods have limitations, such high costs technical challenges, can make accurate diagnosis certain deep-seated tumors difficult. To achieve prognosis, essential continue developing cutting-edge technologies molecular biology imaging.

Язык: Английский

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A QUANTITATIVE ANALYSIS OF HEALTHCARE FRAUD AND UTILIZATION OF AI FOR MITIGATION

Deleted Journal, Год журнала: 2024, Номер 04(07), С. 13 - 36

Опубликована: Июль 29, 2024

Healthcare fraud is an emerging and prevalent problem that threatens the reputability of healthcare system, leading to significant financial charges disrupting patient's care. Conventional prevention techniques include manual audits rule-based systems, which are no longer adequate in contempt sophisticated schemes. The advent advanced technologies like Artificial Intelligence contributes new opportunities confront more effectively. AI-powered solutions voice biometrics scrutinizing distinctive identifiers patterning detect fraudulent activities with greater efficiency accuracy contrast conventional methods. By leveraging Machine Learning algorithms, these systems could incessantly patterns curtail risk false positives, improving overall effectiveness detection. research has attempted exemplify AI implementation providing accessibility availability for reliance aid system by gauging its presents a comprehensive quantitative scrutiny facilitation over system's security threats mitigation. Since building large-scale labelled Medicare datasets, data-centric approach empowers providers reduce paperwork time-consuming settlements policyholders. present outcome proven applying AI-based mitigation strategies significantly influence industry through analysis. Hence, enhancing automating detection capabilities, organizations maintain their capital resources, protect patient data, retain public reliance. Moreover, proposed results highlight AI's potential transmit prospect prevention, facilitating efficient secure system.

Язык: Английский

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The Development of Assistive Robotics: A Comprehensive Analysis Integrating Machine Learning, Robotic Vision, and Collaborative Human Assistive Robots

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 164 - 214

Опубликована: Янв. 1, 2024

Язык: Английский

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