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Artificial intelligence for medicine, surgery, and public health 医学、外科和公共卫生领域的人工智能
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100141
Jagdish Khubchandani, Srikanta Banerjee, Robert Andrew Yockey, Kavita Batra
Artificial Intelligence (AI) has rapidly transformed many sectors, including medicine, surgery, and public health. While AI has a multitude of unique characteristics that differ from the existing and most commonly used healthcare technologies worldwide, the discussion and publications on AI in healthcare have grown exponentially within the past few years. Despite its transformative potential, AI poses several challenges and there are unanswered questions related to the value and impact of AI on consumers, healthcare providers, and health systems. This editorial explores the growing applications of AI and its potential impacts on key entities in the field of healthcare and public health. Also, through this editorial, the journal editors highlight the urgent need for high-quality and real-world setting-based research on the value of AI in healthcare and public health. Finally, as AI will undoubtedly and significantly continue to impact healthcare consumers and systems, the editors are seeking submissions with rigorous and empirical evidence for AI’s impact on health services consumers and providers, and clinical care facilities or public health organizations. The editors believe that unless scholars worldwide generate robust evidence on the value and impact of AI in healthcare, providing the highest benefits of AI to health services consumers will remain an elusive goal.
人工智能(AI)已迅速改变了许多领域,包括医学、外科手术和公共卫生。虽然人工智能具有许多独特的特征,与全球现有的和最常用的医疗保健技术有所不同,但在过去几年中,有关医疗保健领域人工智能的讨论和出版物呈指数级增长。尽管人工智能具有变革潜力,但它也带来了一些挑战,在人工智能对消费者、医疗服务提供者和医疗系统的价值和影响方面还存在一些未解之谜。这篇社论探讨了人工智能日益增长的应用及其对医疗保健和公共卫生领域主要实体的潜在影响。此外,通过这篇社论,期刊编辑们强调,迫切需要对人工智能在医疗保健和公共卫生领域的价值进行基于真实世界环境的高质量研究。最后,由于人工智能无疑将继续对医疗保健消费者和系统产生重大影响,编辑们正在征集关于人工智能对医疗服务消费者和提供者、临床医疗机构或公共卫生组织的影响的严谨实证研究报告。编辑们相信,除非全世界的学者都能就人工智能在医疗保健领域的价值和影响提供有力的证据,否则为医疗服务消费者提供人工智能的最大益处仍将是一个遥不可及的目标。
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引用次数: 0
Artificial Intelligence and the Dehumanization of Patient Care 人工智能与病人护理的非人性化
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100138
Adewunmi Akingbola, Oluwatimilehin Adeleke, Ayotomiwa Idris, Olajumoke Adewole, Abiodun Adegbesan

The integration of artificial intelligence (AI) into healthcare is rapidly transforming patient care, offering numerous advantages in diagnostics, efficiency, and clinical decision-making. However, this technological shift raises significant concerns about the potential erosion of the doctor-patient relationship, a cornerstone of effective medical practice. AI’s increasing role risks depersonalizing healthcare, as the emphasis on data-driven decisions may overshadow the empathy, trust, and personalized care traditionally provided by human clinicians. The "black-box" nature of AI algorithms further exacerbates this issue, as the lack of transparency in AI decision-making processes can undermine patient trust. Additionally, AI systems trained on biased datasets may inadvertently widen health disparities, particularly for underrepresented populations. While AI has the potential to streamline routine tasks and reduce the burden on healthcare providers, it is essential to ensure that these advancements do not come at the cost of the human connection vital to patient care. To address these challenges, future research and development should focus on creating AI systems that enhance, rather than replace, the compassionate aspects of healthcare. This balanced approach is crucial to preserving the integrity of the doctor-patient relationship while harnessing the benefits of AI, ultimately ensuring that technological progress aligns with the core values of medical practice.

人工智能(AI)与医疗保健的结合正在迅速改变患者护理,在诊断、效率和临床决策方面带来了诸多优势。然而,这一技术转变也引发了人们对医患关系可能受到侵蚀的严重担忧,而医患关系是有效医疗实践的基石。人工智能的作用越来越大,有可能使医疗保健失去个性,因为对数据驱动决策的重视可能会掩盖传统上由人类临床医生提供的同理心、信任和个性化护理。人工智能算法的 "黑箱 "性质进一步加剧了这一问题,因为人工智能决策过程缺乏透明度会破坏患者的信任。此外,在有偏见的数据集上训练的人工智能系统可能会无意中扩大健康差距,特别是对代表性不足的人群。虽然人工智能有可能简化常规任务并减轻医疗服务提供者的负担,但必须确保这些进步不会以牺牲对患者护理至关重要的人与人之间的联系为代价。为了应对这些挑战,未来的研究和开发工作应侧重于创建人工智能系统,以增强而非取代医疗保健的人文关怀。这种平衡的方法对于在利用人工智能优势的同时保持医患关系的完整性至关重要,最终确保技术进步与医疗实践的核心价值保持一致。
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引用次数: 0
Artificial Intelligence And Cancer Care in Africa 人工智能与非洲癌症护理
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100132
Adewunmi Akingbola , Abiodun Adegbesan , Olajide Ojo , Jessica Urowoli Otumara , Uthman Hassan Alao

AI's potential to revolutionize oncology through enhanced diagnostics, treatment planning, and patient monitoring is well-documented globally. However, in Africa, its adoption has been slower, albeit steadily progressing. This commentary explores the integration of artificial Intelligence in cancer care across Africa, assessing its current state, challenges and future directions. It highlights significant AI innovations in cancer diagnostics, such as DataPathology, PapsAI, MinoHealth, and Hurone AI, which utilize AI for tissue analysis, cervical cell imaging, disease forecasting, and remote patient monitoring. Despite these advancements, several challenges impede AI's full integration into African healthcare systems. Key issues include data privacy and security, algorithm bias, and insufficient regulatory frameworks. The review emphasizes the necessity of robust data protection policies, representative datasets to mitigate biases, and clear guidelines for AI deployment tailored to the African context. Emerging AI technologies in Africa, such as AI-enhanced telemedicine, mobile health applications, predictive analytics, and virtual tumor boards, show promise in overcoming geographic and resource limitations. These innovations can facilitate remote consultations, continuous patient monitoring, and multidisciplinary collaborations, thereby improving cancer care accessibility and outcomes. Conclusively, recommendations for enhancing AI integration in African cancer care, including investing in data infrastructure, capacity building for healthcare professionals, and fostering international collaborations are discussed. Addressing ethical and regulatory challenges is crucial to ensure responsible and effective use of AI technologies. By leveraging AI, Africa can significantly improve cancer care delivery, reduce mortality rates, and enhance patient quality of life.

在全球范围内,人工智能通过增强诊断、治疗规划和患者监测来彻底改变肿瘤学的潜力已得到充分证实。然而,在非洲,人工智能的应用虽然在稳步推进,但却较为缓慢。本评论探讨了人工智能在非洲癌症治疗中的应用,评估了其现状、挑战和未来方向。它重点介绍了癌症诊断领域的重大人工智能创新,如 DataPathology、PapsAI、MinoHealth 和 Hurone AI,它们利用人工智能进行组织分析、宫颈细胞成像、疾病预测和远程患者监测。尽管取得了这些进步,但人工智能全面融入非洲医疗系统仍面临一些挑战。关键问题包括数据隐私和安全、算法偏差以及监管框架不足。审查强调,有必要制定强有力的数据保护政策、具有代表性的数据集以减少偏差,并制定适合非洲国情的明确的人工智能部署指南。非洲新兴的人工智能技术,如人工智能增强型远程医疗、移动医疗应用、预测分析和虚拟肿瘤委员会,在克服地理和资源限制方面显示出前景。这些创新技术可以促进远程会诊、持续的患者监测和多学科合作,从而改善癌症治疗的可及性和治疗效果。最后,还讨论了在非洲癌症治疗中加强人工智能整合的建议,包括投资数据基础设施、医疗保健专业人员的能力建设以及促进国际合作。应对伦理和监管方面的挑战对于确保负责任地有效利用人工智能技术至关重要。通过利用人工智能,非洲可以显著改善癌症护理服务,降低死亡率,提高患者的生活质量。
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引用次数: 0
The rising threat of counterfeit GLP-1 receptor agonists: Implications for public health 假冒 GLP-1 受体激动剂的威胁日益严重:对公共卫生的影响
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100136
Abdur Rehman, Abdulqadir J. Nashwan

The rising demand for GLP-1 receptor agonists (GLP-1RAs), effective treatments for type 2 diabetes and obesity, has inadvertently led to a proliferation of counterfeit versions. This letter to the editor highlights the significant public health challenges posed by counterfeit GLP-1RAs, including severe risks to patient safety, economic impacts, and the erosion of public trust in the healthcare system. Counterfeit GLP-1RAs often contain incorrect dosages, harmful ingredients, or entirely lack the active ingredients, leading to ineffective treatment and potentially life-threatening complications such as hyperglycemia and cardiovascular issues. The economic burden of counterfeit drugs is also considerable, with healthcare systems incurring substantial costs in managing complications from these illegitimate medications, including hospitalizations and increased surveillance efforts. The drivers of this counterfeit drug problem include regulatory gaps, inadequate enforcement, and the expanding market demand due to rising rates of diabetes and obesity. In conclusion, the proliferation of counterfeit GLP-1RAs represents a critical threat to global health, underscoring the need for comprehensive measures to safeguard the integrity of the pharmaceutical supply chain and ensure patient safety. Addressing this issue requires a multifaceted approach that integrates regulatory oversight, technological innovation, and public education to mitigate the risks posed by counterfeit drugs and restore public trust in the healthcare system.

GLP-1受体激动剂(GLP-1RA)是治疗2型糖尿病和肥胖症的有效药物,随着市场对这种药物的需求不断增加,不经意间导致了假药的泛滥。这封致编辑的信强调了假冒 GLP-1RA 给公共卫生带来的重大挑战,包括对患者安全的严重风险、经济影响以及公众对医疗系统信任度的降低。假冒 GLP-1RA 通常含有不正确的剂量、有害成分或完全不含活性成分,从而导致治疗无效和潜在的危及生命的并发症,如高血糖和心血管问题。假药造成的经济负担也相当可观,医疗保健系统在处理这些非法药物引起的并发症(包括住院治疗和增加监控工作)时需要花费大量成本。造成假药问题的原因包括监管漏洞、执法不力以及糖尿病和肥胖症发病率上升导致的市场需求扩大。总之,假冒 GLP-1RA 的泛滥对全球健康构成了严重威胁,突出表明有必要采取综合措施来保障药品供应链的完整性并确保患者安全。解决这一问题需要采取多方面的方法,将监管监督、技术创新和公众教育结合起来,以降低假药带来的风险,恢复公众对医疗保健系统的信任。
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引用次数: 0
From Scalpels to Algorithms: The Risk of Dependence on Artificial Intelligence in Surgery 从手术刀到算法:外科手术依赖人工智能的风险
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100140
Abiodun Adegbesan, Adewunmi Akingbola, Olusola Aremu, Olajumoke Adewole, John Chukwuemeka Amamdikwa, Uchechukwu Shagaya
Artificial Intelligence (AI) is transforming surgery, advancing robotic-assisted procedures, preoperative risk prediction, and intraoperative decision-making. However, increasing reliance on AI raises concerns, particularly regarding the potential deskilling of surgeons and overdependence on algorithmic recommendations. This over-reliance risks diminishing surgeons' skills, increasing surgical errors, and undermining their decision-making autonomy. The "black-box" nature of many AI systems also presents ethical challenges, as surgeons may feel pressured to follow AI-driven recommendations without fully understanding the underlying logic. Additionally, AI biases from inadequate datasets can result in misdiagnoses and worsen healthcare disparities. While AI offers immense promise, a cautious approach is vital to prevent overdependence. Ensuring that AI enhances rather than replaces human skills in surgery is critical to maintaining patient safety. Ongoing research, ethical considerations, and robust legal frameworks are essential for guiding AI's integration into surgical practice. Surgeons must receive comprehensive training to incorporate AI into their work without compromising clinical judgment. This letter emphasizes the need for clear guidelines, thorough surgeon training, and transparent AI systems to address the risks associated with AI dependence. By taking these steps, healthcare systems can harness the benefits of AI while preserving the essential human aspects of surgical care.
人工智能(AI)正在改变外科手术,推动机器人辅助手术、术前风险预测和术中决策的发展。然而,人们对人工智能的依赖程度越来越高,这引起了人们的担忧,特别是外科医生可能会被裁员,以及过度依赖算法建议。这种过度依赖有可能降低外科医生的技能、增加手术失误并削弱他们的决策自主权。许多人工智能系统的 "黑箱 "性质也带来了伦理方面的挑战,因为外科医生可能会感到有压力,在没有完全理解内在逻辑的情况下,不得不遵循人工智能驱动的建议。此外,数据集不足造成的人工智能偏差可能会导致误诊,并加剧医疗差距。虽然人工智能大有可为,但要防止过度依赖,谨慎行事至关重要。确保人工智能在外科手术中增强而非取代人类技能,对于维护患者安全至关重要。持续的研究、伦理考虑和健全的法律框架对于指导人工智能融入外科手术实践至关重要。外科医生必须接受全面的培训,以便在不影响临床判断的情况下将人工智能融入其工作。这封信强调了明确的指导方针、全面的外科医生培训和透明的人工智能系统的必要性,以应对与人工智能依赖性相关的风险。通过采取这些措施,医疗保健系统可以利用人工智能的优势,同时保留外科护理的基本人文因素。
{"title":"From Scalpels to Algorithms: The Risk of Dependence on Artificial Intelligence in Surgery","authors":"Abiodun Adegbesan,&nbsp;Adewunmi Akingbola,&nbsp;Olusola Aremu,&nbsp;Olajumoke Adewole,&nbsp;John Chukwuemeka Amamdikwa,&nbsp;Uchechukwu Shagaya","doi":"10.1016/j.glmedi.2024.100140","DOIUrl":"10.1016/j.glmedi.2024.100140","url":null,"abstract":"<div><div>Artificial Intelligence (AI) is transforming surgery, advancing robotic-assisted procedures, preoperative risk prediction, and intraoperative decision-making. However, increasing reliance on AI raises concerns, particularly regarding the potential deskilling of surgeons and overdependence on algorithmic recommendations. This over-reliance risks diminishing surgeons' skills, increasing surgical errors, and undermining their decision-making autonomy. The \"black-box\" nature of many AI systems also presents ethical challenges, as surgeons may feel pressured to follow AI-driven recommendations without fully understanding the underlying logic. Additionally, AI biases from inadequate datasets can result in misdiagnoses and worsen healthcare disparities. While AI offers immense promise, a cautious approach is vital to prevent overdependence. Ensuring that AI enhances rather than replaces human skills in surgery is critical to maintaining patient safety. Ongoing research, ethical considerations, and robust legal frameworks are essential for guiding AI's integration into surgical practice. Surgeons must receive comprehensive training to incorporate AI into their work without compromising clinical judgment. This letter emphasizes the need for clear guidelines, thorough surgeon training, and transparent AI systems to address the risks associated with AI dependence. By taking these steps, healthcare systems can harness the benefits of AI while preserving the essential human aspects of surgical care.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100140"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial Intelligence for Pediatric Emergency Medicine 人工智能在儿科急诊医学中的应用
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100137
Mohammed Alsabri , Nicholas Aderinto , Marina Ramzy Mourid , Fatima Laique , Salina Zhang , Noha S. Shaban , Abdalhakim Shubietah , Luis L. Gamboa

Pediatric Emergency Medicine (PEM) addresses the unique needs of children in emergencies. This subspecialty faces significant challenges, including the need for specialized training, patient crowding, and the demand for timely and accurate management. Artificial Intelligence (AI) presents promising solutions by enhancing diagnostic precision and operational efficiency. This review examines current trends and prospects of AI in PEM, focusing on its applications, benefits, challenges, and transformative potential. The review highlights AI’s role in overcoming PEM challenges and its future opportunities. Key AI applications in PEM include early sepsis detection, improving triage accuracy, predicting injuries, and supporting diagnostics. AI models show significant potential in forecasting clinical outcomes, optimizing resource management, and improving patient care. Despite these benefits, challenges remain, including the need for specialized training for physicians and the integration of AI systems into clinical practice. Yet, AI holds considerable promise for advancing PEM through enhanced diagnostic tools, more efficient patient management, and improved clinical decision support. Continued advancements and collaborations between AI researchers and pediatric emergency practitioners are essential to fully realize AI’s potential in this field.

儿科急诊医学(PEM)满足儿童在紧急情况下的独特需求。这个亚专科面临着巨大的挑战,包括对专业培训的需求、病人拥挤以及对及时准确管理的要求。人工智能(AI)通过提高诊断精确度和操作效率,提供了前景广阔的解决方案。本综述探讨了人工智能在 PEM 领域的当前趋势和前景,重点关注其应用、优势、挑战和变革潜力。综述强调了人工智能在克服 PEM 挑战方面的作用及其未来机遇。人工智能在急诊急救中的主要应用包括早期败血症检测、提高分流准确性、预测伤害和支持诊断。人工智能模型在预测临床结果、优化资源管理和改善患者护理方面显示出巨大潜力。尽管有这些优势,但挑战依然存在,包括需要对医生进行专门培训以及将人工智能系统融入临床实践。然而,通过增强诊断工具、提高患者管理效率和改善临床决策支持,人工智能在推进 PEM 方面大有可为。要充分发挥人工智能在这一领域的潜力,人工智能研究人员和儿科急诊医师之间的持续进步与合作至关重要。
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引用次数: 0
The promise of artificial intelligence and internet of things in oral cancer detection 人工智能和物联网在口腔癌检测中的应用前景
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100130
Amol S. Dhane

The significance of artificial intelligence (AI) and the internet of things (IoT) in improving oral cancer detection is critically assessed in this letter. Oral cancer is a major worldwide health concern that is frequently detected at a late stage, resulting in a poor prognosis. AI techniques, in particular machine learning and deep learning models, show great promise for accurately assessing digital images and histopathology slides, assisting physicians in risk assessment and early identification. Furthermore, real-time monitoring and surveillance are made possible by IoT-enabled devices, which gather important patient data for the early identification of indications of oral cancer. Furthermore, the performance and efficacy of diagnosis have been improved by developments in image processing algorithms, which helps to avoid delayed diagnosis. Big data analytics and the application of salivary biomarkers enhance early detection initiatives. To battle oral cancer, a variety of AI and IoT strategies are being investigated, in addition to other AI uses. Although encouraging developments, application in clinical practice will not be successful unless issues with validation, standardization, data privacy and regulatory compliance are resolved. Working together, healthcare stakeholders can promote innovation, validate techniques and get over current obstacles. To reduce the prevalence of oral cancer, future directions include the creation of multimodal imaging methods and their incorporation into population-based screening initiatives. We can move closer to early detection, individualized therapy and prevention of oral cancer by utilizing AI and IoT, which will ultimately improve patient outcomes.

本信对人工智能(AI)和物联网(IoT)在改善口腔癌检测方面的意义进行了认真评估。口腔癌是全球关注的一大健康问题,往往在晚期才被发现,导致预后不良。人工智能技术,特别是机器学习和深度学习模型,在准确评估数字图像和组织病理学切片、协助医生进行风险评估和早期识别方面显示出巨大的前景。此外,物联网设备使实时监测和监控成为可能,这些设备可收集重要的患者数据,用于早期识别口腔癌的迹象。此外,图像处理算法的发展也提高了诊断的性能和效率,有助于避免延误诊断。大数据分析和唾液生物标志物的应用加强了早期检测措施。为了与口腔癌作斗争,除其他人工智能应用外,各种人工智能和物联网战略也在研究之中。虽然发展令人鼓舞,但除非解决验证、标准化、数据隐私和监管合规等问题,否则临床实践中的应用不会成功。医疗保健利益相关方共同努力,就能促进创新、验证技术并克服当前的障碍。为了降低口腔癌的发病率,未来的发展方向包括创建多模态成像方法,并将其纳入人群筛查计划。通过利用人工智能和物联网,我们可以实现口腔癌的早期检测、个性化治疗和预防,最终改善患者的治疗效果。
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引用次数: 0
The role of artificial intelligence in enhancing nurses' work-life balance 人工智能在促进护士工作与生活平衡方面的作用
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100135
Moustaq Karim Khan Rony , Daifallah M. Alrazeeni , Fazila Akter , Latifun Nesa , Dipak Chandra Das , Muhammad Join Uddin , Jeni Begum , Most. Tahmina Khatun , Md. Abdun Noor , Sumon Ahmad , Sabren Mukta Tanha , Tuli Rani Deb , Mst. Rina Parvin

Nursing, a cornerstone of healthcare, is a profession characterized by its dedication to patient well-being. However, the demanding nature of nursing often takes a toll on work-life balance. This commentary investigates how artificial intelligence (AI) could significantly impact the healthcare sector, particularly by enhancing the work-life balance of nurses. It highlights how AI can greatly lessen administrative tasks, improve clinical decision-making, and support remote patient monitoring, ultimately helping nurses achieve a more balanced work-life dynamic. The advancement of AI in healthcare presents a strong opportunity to improve nurses' work-life balance. Our comprehensive conceptual framework illustrates how AI can transform nursing practice, offering nurses newfound efficiency and flexibility. By responsibly integrating AI technologies, healthcare institutions can empower nurses to excel in their roles while enjoying a more sustainable work-life equilibrium. This commentary serves as a roadmap for embracing the potential of AI, not as a replacement for nurses, but as a valuable ally in fostering a better future for both nurses and the patients they serve.

护理是医疗保健的基石,是一个以全心全意为病人服务为特点的职业。然而,护理工作的艰巨性往往会影响工作与生活的平衡。这篇评论探讨了人工智能(AI)如何对医疗保健行业产生重大影响,尤其是如何加强护士的工作与生活平衡。它强调了人工智能如何能够大大减轻行政任务、改善临床决策并支持远程病人监护,最终帮助护士实现更平衡的工作与生活动态。人工智能在医疗保健领域的发展为改善护士的工作与生活平衡提供了一个很好的机会。我们的综合概念框架说明了人工智能如何改变护理实践,为护士提供新发现的效率和灵活性。通过负责任地整合人工智能技术,医疗机构可以让护士在享受更可持续的工作与生活平衡的同时,在自己的岗位上发挥所长。本评论可作为拥抱人工智能潜力的路线图,人工智能不是护士的替代品,而是为护士和他们所服务的患者创造更美好未来的宝贵盟友。
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引用次数: 0
Artificial intelligence for hearing loss prevention, diagnosis, and management 人工智能用于听力损失的预防、诊断和管理
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100133
Jehad Feras AlSamhori , Abdel Rahman Feras AlSamhori , Rama Mezyad Amourah , Yara AlQadi , Zina Wael Koro , Toleen Ramzi Abdallah Haddad , Ahmad Feras AlSamhori , Diala Kakish , Maya Jamal Kawwa , Margaret Zuriekat , Abdulqadir J. Nashwan

This paper explores the transformative impact of artificial intelligence (AI), particularly machine learning (ML), on diagnosing and treating hearing loss, which affects over 5% of the global population across all ages and demographics. AI encompasses various applications, from natural language processing models like ChatGPT to image recognition systems; however, this paper focuses on ML, a subfield of AI that can revolutionize audiology by enhancing early detection, formulating personalized rehabilitation plans, and integrating electronic health records for streamlined patient care. The integration of ML into audiometry, termed "computational audiology," allows for automated, accurate hearing tests. AI algorithms can process vast data sets, provide detailed audiograms, and facilitate early detection of hearing impairments. Research shows ML's effectiveness in classifying audiograms, conducting automated audiometry, and predicting hearing loss based on noise exposure and genetics. These advancements suggest that AI can make audiological diagnostics and treatment more accessible and efficient. The future of audiology lies in the seamless integration of AI technologies. Collaborative efforts between audiologists, AI experts, and individuals with hearing loss are essential to overcome challenges and leverage AI's full potential. Continued research and development will enhance AI applications in audiology, improving patient outcomes and quality of life worldwide.

本文探讨了人工智能(AI),尤其是机器学习(ML)对听力损失诊断和治疗的变革性影响。人工智能包含各种应用,从自然语言处理模型(如 ChatGPT)到图像识别系统;然而,本文重点关注的是人工智能的一个子领域--ML,它可以通过加强早期检测、制定个性化康复计划以及整合电子健康记录以简化患者护理来彻底改变听力学。将人工智能整合到听力测量中,即 "计算听力学",可实现自动、准确的听力测试。人工智能算法可以处理庞大的数据集,提供详细的听力图,并有助于早期发现听力障碍。研究表明,人工智能在听力图分类、自动测听以及根据噪音暴露和遗传学预测听力损失方面非常有效。这些进步表明,人工智能可以使听力诊断和治疗更加方便、高效。听力学的未来在于人工智能技术的无缝整合。听力学家、人工智能专家和听力损失患者之间的合作对于克服挑战和充分发挥人工智能的潜力至关重要。持续的研究和开发将提高人工智能在听力学中的应用,改善全球患者的治疗效果和生活质量。
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引用次数: 0
Towards equitable renal care: Strategies for enhancing kidney transplantation in Africa 实现公平的肾脏护理:加强非洲肾移植的战略
Pub Date : 2024-08-01 DOI: 10.1016/j.glmedi.2024.100131
Ikponmwosa Jude Ogieuhi, Nicholas Aderinto, Gbolahan Olatunji, Emmanuel Kokori, Adetola Emmanuel Babalola, Komolafe Babajide Ayodeji, Ajekiigbe Victor Oluwatomiwa, Muhammadul-Awwal Irodatullah Bisola, Ibukunoluwa V. Ishola, Ojabo Rebecca, Irene Ojapah

Chronic kidney disease (CKD) is defined as the presence of kidney damage persisting for 3 months or more. Kidney transplantation stands as a vital intervention for individuals grappling with end-stage renal disease (ESRD) in Africa, offering the promise of extended life and improved quality of life. However, numerous challenges hinder its widespread implementation across the continent. This paper explored kidney transplantation in Africa, aiming to illuminate key strategies for bridging gaps and building pathways to enhanced renal care. There is a disproportionate burden of CKD on the region's population. Therefore, there is a critical need for early diagnosis and intervention. This paper outlines comprehensive strategies for improving kidney transplantation in Africa. Results indicate that financial support systems, infrastructure enhancement, public awareness campaigns, and legal frameworks are essential for addressing renal care barriers. Active measures such as government subsidy programs, international funding collaboration, and engagement with community leaders are highlighted as effective approaches. Drawing from global standards and best practices, the paper shows the importance of tailored approaches that address Africa's unique socio-economic and healthcare landscape. By leveraging collaborative efforts, regulatory frameworks, and public engagement, African nations can overcome barriers to kidney transplantation and pave the way for equitable access to life-saving treatment.

慢性肾脏病(CKD)是指肾脏损伤持续 3 个月或更长时间。对于非洲终末期肾病(ESRD)患者来说,肾移植是一项重要的干预措施,有望延长生命并提高生活质量。然而,众多挑战阻碍了肾移植在非洲大陆的广泛实施。本文探讨了非洲的肾移植问题,旨在阐明缩小差距和建立加强肾病治疗途径的关键战略。该地区人口的慢性肾脏病负担过重。因此,迫切需要早期诊断和干预。本文概述了改善非洲肾移植的综合战略。结果表明,财政支持系统、基础设施改善、公众宣传活动和法律框架对于解决肾脏护理障碍至关重要。政府补贴计划、国际资金合作和社区领袖参与等积极措施被强调为有效的方法。本文借鉴了全球标准和最佳实践,说明了针对非洲独特的社会经济和医疗保健状况量身定制方法的重要性。通过利用合作努力、监管框架和公众参与,非洲国家可以克服肾移植的障碍,为公平获得救命治疗铺平道路。
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Journal of Medicine, Surgery, and Public Health
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