Journal of Medicine, Surgery, and Public Health最新文献_第6页

Leveraging artificial intelligence to improve health insurance access and address disparities in rural Africa 利用人工智能改善医疗保险获取，解决非洲农村的差距问题

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-15 DOI: 10.1016/j.glmedi.2024.100172

Olajumoke Adesola Adewole , Adewunmi Akingbola , Abiodun Christopher Adegbesan , Theodora Nkechi Ndu-Esekea, Samiat Bisodun Olalemi

Urban-rural inequalities in access to healthcare services remain a significant obstacle to development in Africa. Rural communities are more affected by the poor state of the African healthcare system, They lack essential healthcare facilities, have a shortage of healthcare workforce, inadequate transportation facilities that keep them isolated, and high out-of-pocket healthcare costs which put them at risk of the catastrophic effect of healthcare expenditure. Several health insurance schemes have been designed in an attempt to meet the SDG 3.8 goal of universal health coverage and access to quality, safe, effective, and affordable health care in rural communities. However, despite these efforts, there are still significant challenges with access and utilization of these insurance schemes. Artificial intelligence (AI) has been integrated into different areas of healthcare including medical imaging and diagnosis, surgery, and so on, and has improved health outcomes significantly. If adequately leveraged, AI can be useful in risk assessment and in automating claim process, thereby improving accessibility and utilization of health insurance in rural communities. It can also be used in protecting resources for rural healthcare by detecting fraud, thereby increasing the trust of the community in the insurer. Integration of AI into healthcare services can be very useful in improve health insurance access and reducing health disparities in rural communities thus aiding in the fulfilment of universal health coverage.

在获得保健服务方面的城乡不平等仍然是非洲发展的一个重大障碍。农村社区受到非洲卫生保健系统状况不佳的影响更大，他们缺乏基本的卫生保健设施，卫生保健工作人员短缺，交通设施不足使他们与外界隔绝，自费医疗保健费用高，使他们面临卫生保健支出灾难性影响的风险。为实现可持续发展目标3.8关于在农村社区实现全民健康覆盖和获得优质、安全、有效和负担得起的医疗保健的目标，已经设计了若干医疗保险计划。然而，尽管做出了这些努力，在获得和利用这些保险计划方面仍然存在重大挑战。人工智能（AI）已经被整合到医疗保健的不同领域，包括医学成像和诊断、手术等，并显著改善了健康结果。如果加以充分利用，人工智能可以在风险评估和自动索赔过程中发挥作用，从而改善农村社区医疗保险的可及性和利用率。它还可以通过检测欺诈来保护农村医疗保健资源，从而增加社区对保险公司的信任。将人工智能整合到医疗保健服务中，对于改善医疗保险获取和缩小农村社区的健康差距非常有用，从而有助于实现全民健康覆盖。

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引用次数: 0

Artificial intelligence for access to primary healthcare in rural settings 在农村环境中获得初级保健的人工智能

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-15 DOI: 10.1016/j.glmedi.2024.100173

Md Faiazul Haque Lamem, Muaj Ibne Sahid, Anika Ahmed

Artificial Intelligence (AI) may enhance access to primary health care in rural settings, especially in areas with an underserved and rural populace, due to systemic challenges in infrastructure inadequacies, shortages of trained professionals, and poor preventive measures. This paper discusses the transformative roles of AI technologies in the efforts toward bridging these gaps by improving healthcare delivery and access. With the rise of machine learning (ML) and natural language processing (NLP), AI applications may enhance diagnostic accuracy, speed up and facilitate patient interfaces, and perform resource management more optimally. This list of benefits seems promising, but the realization of AI in healthcare faces quite a few challenges: it requires ethical considerations, assurance of data safety, and sound legal frameworks. While AI, Internet of Things (IoT), and mobile health (mHealth) technologies create innovative solutions in remote monitoring and consultation, these technologies help promote prevention. Realizing the full potential of AI in rural health is thus a challenge in both infrastructural and socio-economic spheres, requiring active collaboration. This present study indicates that it is high time there was an urgent need for high-quality research with real-world evaluation regarding the effectiveness of AI in bringing improvement in health outcomes among people in rural settings.

由于基础设施不足、训练有素的专业人员短缺和预防措施不力等系统性挑战，人工智能（AI）可能会增加农村地区获得初级卫生保健的机会，特别是在服务不足的地区和农村人口。本文讨论了人工智能技术在通过改善医疗服务和获取来弥合这些差距方面的变革性作用。随着机器学习（ML）和自然语言处理（NLP）的兴起，人工智能应用可以提高诊断准确性，加快和便利患者界面，并更优化地执行资源管理。这些好处似乎很有希望，但人工智能在医疗保健领域的实现面临着相当多的挑战：它需要道德考虑、数据安全保证和健全的法律框架。人工智能、物联网（IoT）和移动医疗（mHealth）技术在远程监测和咨询方面创造了创新的解决方案，这些技术有助于促进预防。因此，在基础设施和社会经济领域充分发挥人工智能在农村卫生领域的潜力是一项挑战，需要积极合作。目前的这项研究表明，现在迫切需要进行高质量的研究，并对人工智能在改善农村人口健康状况方面的有效性进行实际评估。

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引用次数: 0

Suicide attempts in Bangladesh: Prevalence, trends, and disparities 孟加拉国的自杀企图：流行、趋势和差异

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-13 DOI: 10.1016/j.glmedi.2024.100170

Tonmoy Alam Shuvo , Kabir Hossain , Asma-Ul-Hosna , Dipu Rani Dey

Suicide attempts are a major public health issue, influenced by a range of factors. Assessing the prevalence of suicide attempts in Bangladesh is crucial for understanding the country's mental health landscape. We searched multiple databases and included 11 articles in the meta-analysis. We used a random-effects model to pool prevalence data. We assessed between-study heterogeneity through the Q-test and I² statistics and conducted subgroup analyses. To evaluate potential publication bias, we utilized a funnel plot and Egger's test. Additionally, meta-regression was performed to identify sources of heterogeneity, while sensitivity analysis was conducted to assess the robustness of the findings. Study quality was assessed using the Joanna Briggs Institute (JBI) tools. The pooled prevalence of suicide attempts in Bangladesh was 4.25 % (95 % CI: 2.28–6.22). The prevalence among males was 3.36 %, while females had a higher prevalence of 4.17 %. The pooled odds ratio for the risk of suicide attempts among females was 1.16 (95 % CI: 0.41–1.91), implying that females were at higher risk than males. We found that the pooled prevalence of suicide attempts among individuals aged 18 and above was 3.42 %. The analysis also uncovered a concerning upward trend in suicide attempts over recent years. The prevalence stood at 3.88 % from 2010 to 2016 and increased to 4.29 % between 2017 and 2023. The pooled prevalence of suicide attempts in Bangladesh revealed significant gender disparities, and a concerning upward trend in recent years, underscoring an urgent need for attention.

自杀企图是一个重大的公共卫生问题，受到一系列因素的影响。评估孟加拉国自杀企图的流行程度对于了解该国的心理健康状况至关重要。我们检索了多个数据库，在meta分析中纳入了11篇文章。我们使用随机效应模型来汇总患病率数据。我们通过q检验和I²统计来评估研究间异质性，并进行亚组分析。为了评估潜在的发表偏倚，我们使用了漏斗图和Egger检验。此外，进行meta回归以确定异质性的来源，同时进行敏感性分析以评估研究结果的稳健性。使用乔安娜布里格斯研究所（JBI）工具评估研究质量。孟加拉国自杀企图的总患病率为4.25% %（95% % CI: 2.28-6.22）。男性患病率为3.36 %，女性患病率为4.17 %。女性自杀企图风险的合并优势比为1.16(95 % CI: 0.41-1.91)，这意味着女性的风险高于男性。我们发现18岁及以上个体的总自杀企图率为3.42 %。该分析还揭示了近年来自杀企图的上升趋势。2010 - 2016年患病率为3.88 %，2017 - 2023年上升至4.29 %。孟加拉国自杀企图的总体流行率显示出显著的性别差异，以及近年来令人担忧的上升趋势，强调了迫切需要引起注意。

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引用次数: 0

Targeted violence against community health workers: A critical barrier to Pakistan’s polio eradication goals 针对社区卫生工作者的针对性暴力：巴基斯坦实现根除脊髓灰质炎目标的一个重大障碍

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-12 DOI: 10.1016/j.glmedi.2024.100169

Rafay Ali Syed, Javaria Qazi

Workplace violence is a significant occupational risk faced by healthcare personnel in community-based settings, posing a global public health threat. Pakistan, one of the few countries, where polio remains endemic has faced targeted violence against polio workers, hindering its progress in eradicating the disease. This violence has profoundly impacted vaccination campaigns, leading to a resurgence of polio cases and the tragic loss of over 200 polio vaccination workers and security officials in recent years. Such violence not only endangers lives but also hampers vaccination initiatives creating fear among workers and reducing immunization coverage, particularly in high-risk areas. The history of these attacks intensified by a breach of trust has compounded resistance from militant groups and the spread of misinformation. Cultural norms, gender-based resistance, and socio-economic vulnerabilities further impede vaccination efforts. This letter proposes the use of community-based approaches such as employing voluntary community mobilizers (VCMs) to enhance public trust and vaccination coverage through strategies including the establishment of polio immunization centers in vulnerable areas, strengthening multi-sectoral partnerships, involving local influencers to address community concerns and implementing safety measures and incentives for health workers. These strategies aim to improve worker safety, promote vaccine acceptance, and ensure sustainable progress toward a polio-free Pakistan.

工作场所暴力是社区卫生保健人员面临的一项重大职业风险，对全球公共卫生构成威胁。巴基斯坦是脊髓灰质炎仍然流行的少数几个国家之一，它面临针对脊髓灰质炎工作人员的有针对性的暴力行为，阻碍了其根除该疾病的进展。这种暴力严重影响了疫苗接种运动，导致脊髓灰质炎病例死灰复燃，近年来有200多名脊髓灰质炎疫苗接种工作者和安全官员不幸丧生。这种暴力行为不仅危及生命，而且妨碍疫苗接种行动，在工作人员中造成恐惧，降低免疫接种覆盖率，特别是在高风险地区。这些袭击的历史由于信任的破坏而加剧，加剧了激进组织的抵制和错误信息的传播。文化规范、基于性别的抵抗和社会经济脆弱性进一步阻碍了疫苗接种工作。这封信建议采用以社区为基础的方法，例如雇用志愿社区动员者（VCMs），通过在脆弱地区建立脊髓灰质炎免疫中心、加强多部门伙伴关系、让当地有影响力的人参与解决社区关切以及实施安全措施和对卫生工作者的激励措施等战略，提高公众信任和疫苗接种覆盖率。这些战略旨在改善工作人员的安全，促进疫苗接受，并确保在巴基斯坦实现无脊髓灰质炎方面取得可持续进展。

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引用次数: 0

3D printing of cancer models for drug discovery: Advancements, challenges, and future perspectives 用于药物发现的3D打印癌症模型：进展、挑战和未来展望

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-10 DOI: 10.1016/j.glmedi.2024.100165

Tolu Fanibuyan, Abdulbasit Opeyemi Muili, Alimi Kehinde Hikmat, Akinmeji Ayodeji, Ridwanullah Ajedamola Lawal, Mubarak Jolayemi Mustapha, Piel Panther Kuol

The advent of 3D printing technology has a great role in cancer research, offering massive opportunities for drug delivery and development. This commentary provides a well-detailed review of the advancements in 3D printing of cancer models, details their application in imitating the complex tumor microenvironment, and enables more meticulous pre-clinical drug testing. We discuss the various 3D printing techniques like “stereolithography”, “selective laser sintering”, and “fused deposition modeling” with their advantages, effects, and limitations. The commentary also makes headway on the critical problem in these vascular networks. In extension, we explore the future perspectives of 3D-printed cancer models, emphasizing the potential for personalized medicine and high–throughput screening. By accentuating these advancements and challenges, we aim to provide a roadmap for future research and development in the use of 3D printing for cancer drug discovery, contributing to more effective and patient-centric cancer treatments.

3D打印技术的出现在癌症研究中发挥了重要作用，为药物输送和开发提供了巨大的机会。这篇评论详细回顾了3D打印癌症模型的进展，详细介绍了它们在模拟复杂肿瘤微环境中的应用，并使临床前药物测试更加细致。我们讨论了各种3D打印技术，如“立体光刻”、“选择性激光烧结”和“熔融沉积建模”，以及它们的优势、效果和局限性。评论也在这些血管网络的关键问题上取得进展。此外，我们还探讨了3d打印癌症模型的未来前景，强调了个性化医疗和高通量筛查的潜力。通过强调这些进步和挑战，我们的目标是为使用3D打印进行癌症药物发现的未来研究和开发提供路线图，为更有效和以患者为中心的癌症治疗做出贡献。

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引用次数: 0

Association of social participation with physical and mental health status among Indian adults 印度成年人的社会参与与身心健康状况的关系

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-09 DOI: 10.1016/j.glmedi.2024.100166

Subhadeep Saha , Priya Das , Tanu Das , Partha Das , Tamal Basu Roy

Introductions

Social participation in different activities for individual older adult people increases the quality of life. But sometimes their age-related physical ailments and their background socio-demographic characteristics create barriers to participation in different societal activities. Little is known about what types of health and background conditions affect social participation in India. Therefore, the study inspects the prospective association between low social participation and different variables based on health and background strata among Indian people aged ≥45 years.

Methods

The current study applied cross-sectional data from the first wave (2017-18) of LASI. The main purpose of the survey was to provide knowledge about the health, well-being, and socio-economic condition of Indian middle-aged and older adults. A sample of 55,449 middle-aged and older adults was viewed for analysis. Multivariable logistic regression models were estimated to find the odds of low social participation over explanatory variables.

Results

In this study, the likelihood of low social participation was positively associated with the risk of having low Activities in Daily Living [AOR: 1.16, CI: 1.05-1.27] and cognitive impairment [AOR:1.69, CI:1.55-1.84]. The likelihood of low social participation was notably higher among those who revealed the following health conditions, i.e., bone/joint surgery [AOR:1.28, CI:1.02-1.59], feeling depressed [AOR:1.15, CI:1.06-1.24], and poor eye-sight for distance-seeing [AOR:1.19, CI:1.07-1.32].

Conclusions

Quality care of individuals to combat several diseases and enhance their physical and mental health will reduce the incidence of low social participation. Opportunities in societal neighbourhoods may facilitate more involvement in social life.

对老年人个人来说，参加不同的社会活动可以提高生活质量。但有时他们与年龄有关的身体疾病和他们的背景社会人口特征会对参与不同的社会活动造成障碍。在印度，人们对什么样的健康和背景条件影响社会参与知之甚少。因此，本研究考察了印度≥45岁人群中基于健康和背景阶层的不同变量与低社会参与度之间的潜在关联。方法本研究采用LASI第一波（2017-18）的横断面数据。调查的主要目的是提供有关印度中老年成年人的健康、福祉和社会经济状况的知识。研究人员对55,449名中老年人的样本进行了分析。估计多变量逻辑回归模型发现低社会参与的几率高于解释变量。结果在本研究中，社会参与度低的可能性与日常生活活动低的风险[AOR: 1.16, CI: 1.05-1.27]和认知障碍[AOR:1.69, CI:1.55-1.84]呈正相关。有以下健康状况者，即骨关节手术[AOR:1.28, CI:1.02-1.59]、情绪低落[AOR:1.15, CI:1.06-1.24]、远距离视力差[AOR:1.19, CI:1.07-1.32]，其社会参与程度较低的可能性显著较高。结论对个体进行高质量的护理，与多种疾病作斗争，增强个体的身心健康，可以降低社会参与率低的发生率。社会社区的机会可能有助于更多地参与社会生活。

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引用次数: 0

Role of folate receptor and CD44 in targeting of docetaxel and paclitaxel fabricated conjugates for efficient cancer therapy 叶酸受体和CD44在靶向多西紫杉醇和紫杉醇合成偶联物中的作用，用于有效的癌症治疗

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-07 DOI: 10.1016/j.glmedi.2024.100163

Amol Tatode , Pranav R. Agrawal , Jayshree Taksande , Mohammad Qutub , Tanvi Premchandani , Milind Umekar , Kishor Danao

A novel target folate receptor and CD44 receptor are deliberated for effective as chemotherapeutic agents. Usually, these receptors are play a vital role in the functional condition such as cell adhesion, healing and inflammation process. Thus, to treat cancerous cell is most difficult by traditional method can be most easily treated with the use of folic acid and hyaluronic acid-linked chemotherapeutics. Also, the various problems associated with Paclitaxel and Docetaxel like inability to deliver at specific target, affection towards healthy cells, poor aqueous solubility, side effects and acquired drug resistance can be minimized with the use of this targeting technique. In recent years, various studies have been ongoing on minimizing the problems associated with the delivery of docetaxel and paclitaxel, and targeting therapy is one of them. This review gives a clear picture of the concept of targeting therapy for the efficient delivery of docetaxel and paclitaxel using folic and hyaluronic acid conjugates.

一种新的靶叶酸受体和CD44受体被认为是有效的化疗药物。通常，这些受体在细胞粘附、愈合和炎症等功能状态中起着至关重要的作用。因此，要用传统方法治疗癌细胞最为困难，可以用最容易的叶酸和透明质酸联合化疗药物进行治疗。此外，紫杉醇和多西紫杉醇相关的各种问题，如无法在特定靶点递送，对健康细胞的影响，水溶性差，副作用和获得性耐药性，可以通过使用这种靶向技术最小化。近年来，各种研究正在进行，以尽量减少与多西紫杉醇和紫杉醇递送相关的问题，靶向治疗是其中之一。本文综述了叶酸和透明质酸缀合物靶向治疗多西紫杉醇和紫杉醇有效递送的概念。

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引用次数: 0

Unifying and linking data sources in medical and public health research 统一和连接医疗和公共卫生研究中的数据源

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-06 DOI: 10.1016/j.glmedi.2024.100164

Kavita Batra, Vidhani S. Goel, Ana L. Reyes, Bertille Assoumou, Dodds P. Simangan, Farooq Abdulla, Deborah A. Kuhls

Data linkage methods, including probabilistic, deterministic, and hybrid are critical for linking medical and public health records, expanding data scope, and improving research outcomes. These methods differ in accuracy, efficiency, and scalability. This letter seeks to identify best practices for enhancing data quality and linkage rates in healthcare and public health research using these techniques. Data linkage enhances data quality by removing duplicates and correcting artifacts, facilitates cost-effective longitudinal studies by integrating existing data, and supports public health through person-oriented statistics and disease registries. Tools like "RecordLinkage" in R and EpiLink have advanced linkage accuracy, particularly in epidemiological studies. A PubMed search in November 2023 identified 176 studies, with 29 meeting inclusion criteria. Hybrid methods showed superior accuracy, with some studies achieving over 90 % linkage rates. Emerging AI-driven methods can further improved scalability, efficiency, and automation, employing privacy-preserving techniques like federated learning to address confidentiality concerns. However, challenges such as inconsistent data, incomplete identifiers, and technical complexities remain, emphasizing the need for standardized protocols and robust ethical frameworks. In low- and middle-income countries (LMICs), tailored strategies such as enhancing health information systems, adopting open-source tools, and fostering regional collaborations are essential to address resource constraints. Initiatives like the Western Australian Data Linkage System exemplify the potential impact of linkage on healthcare and public health. Future research should focus on refining methods, integrating diverse datasets, and leveraging AI to improve linkage efficiency and reliability. By adopting best practices, data linkage can enhance decision-making, optimize interventions, and advance global health research.

包括概率、确定性和混合在内的数据链接方法对于链接医疗和公共卫生记录、扩大数据范围和改进研究成果至关重要。这些方法在准确性、效率和可伸缩性方面有所不同。本信函旨在确定使用这些技术提高医疗保健和公共卫生研究中的数据质量和关联率的最佳做法。数据链接通过消除重复和纠正人为因素提高数据质量，通过整合现有数据促进具有成本效益的纵向研究，并通过面向个人的统计和疾病登记支持公共卫生。像R中的“RecordLinkage”和EpiLink这样的工具具有高级的链接准确性，特别是在流行病学研究中。2023年11月的PubMed检索确定了176项研究，其中29项符合纳入标准。混合方法显示出更高的准确性，一些研究达到了90% %以上的连锁率。新兴的人工智能驱动的方法可以进一步提高可扩展性、效率和自动化，采用联邦学习等隐私保护技术来解决机密性问题。然而，诸如数据不一致、标识符不完整和技术复杂性等挑战仍然存在，这强调了对标准化协议和健全的道德框架的需求。在低收入和中等收入国家，加强卫生信息系统、采用开源工具和促进区域合作等量身定制的战略对于解决资源限制至关重要。像西澳大利亚数据联系系统这样的倡议体现了联系对保健和公共卫生的潜在影响。未来的研究应侧重于改进方法，整合不同的数据集，并利用人工智能来提高链接的效率和可靠性。通过采用最佳做法，数据联系可以加强决策，优化干预措施，并推进全球卫生研究。

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引用次数: 0

Multilevel determinants of linkage to care among pregnant women with opioid use disorder 阿片类药物使用障碍孕妇与护理相关的多水平决定因素

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-03 DOI: 10.1016/j.glmedi.2024.100162

Olajumoke Olarewaju, Samuel Tundealao

Opioid use disorder (OUD) in pregnancy poses considerable risks for both the mother and the child, with rising opioid use among women of reproductive age in the United States. Although OUD is treatable, pregnant individuals frequently encounter obstacles like stigma, legal issues, and inadequate access to healthcare. This commentary examines the factors influencing access to treatment services for pregnant individuals with OUD. The proposed conceptual framework using the socioecological model emphasizes the intricate relationships among these multi-level determinants. At the individual level, social expectations of motherhood, internalized stigma, previous healthcare experiences, insufficient understanding of treatment alternatives, and absence of health insurance frequently establish substantial obstacles to care. At the interpersonal level, healthcare personnel's attitudes, training, and communication are crucial in establishing trust and promoting treatment adherence, while supportive social networks and family involvement enhance care engagement and resilience. Structurally, the systemic constraints, including the variability in Medicaid coverage, geographic inequities, and inadequate integration of prenatal and addiction care, impede access, exacerbated by punitive policies that stigmatize substance use during pregnancy. Comprehending these dynamics can guide treatments designed to enhance treatment linkage and results. Advocating for a compassionate, patient-centered methodology within healthcare systems is crucial for tackling this escalating public health epidemic and mitigating the stigma associated with opioid use during pregnancy.

怀孕期间阿片类药物使用障碍（OUD）对母亲和孩子都构成相当大的风险，在美国育龄妇女中阿片类药物的使用正在增加。虽然OUD是可以治疗的，但孕妇经常会遇到诸如耻辱、法律问题和无法获得医疗保健等障碍。本评论探讨了影响孕妇OUD患者获得治疗服务的因素。使用社会生态学模型提出的概念框架强调了这些多层次决定因素之间的复杂关系。在个人层面，社会对母性的期望、内化的耻辱感、以前的医疗保健经历、对治疗替代方案的了解不足以及缺乏医疗保险往往会对护理造成重大障碍。在人际层面上，医护人员的态度、培训和沟通对于建立信任和促进治疗依从性至关重要，而支持性社会网络和家庭参与则增强了护理参与和复原力。从结构上看，系统性的制约因素，包括医疗补助覆盖范围的差异、地域不平等以及产前和成瘾护理的不充分整合，阻碍了获取，而对怀孕期间药物使用进行污名化的惩罚性政策又加剧了这一点。了解这些动态可以指导治疗设计，以加强治疗联系和效果。在卫生保健系统内倡导一种富有同情心、以患者为中心的方法，对于应对这一不断升级的公共卫生流行病和减轻与怀孕期间使用阿片类药物相关的耻辱感至关重要。

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引用次数: 0

Large language models for improving cancer diagnosis and management in primary health care settings 用于改善初级卫生保健机构癌症诊断和管理的大型语言模型

Journal of Medicine, Surgery, and Public Health

Pub Date : 2024-12-01 DOI: 10.1016/j.glmedi.2024.100157

Albert Andrew, Ethan Tizzard

Cancer remains a leading cause of death globally, but diagnosing and treating it is often challenging. Barriers such as multiple consultations, overburdened healthcare systems, and limited cancer-specific training among primary health care clinicians significantly delay diagnoses and worsen outcomes. To address these challenges, health care must enhance patient and clinician knowledge while minimizing diagnostic and treatment delays. Emerging technologies, particularly artificial intelligence (AI), hold great promise in revolutionising cancer care by improving diagnosis, education, and patient management. Large language models (LLMs) such as ChatGPT offer exciting potential to enhance cancer care in three key areas: clinical decision-making, patient education and engagement, and access to oncology research. Studies suggest that ChatGPT-4's oncology-related performance approaches that of medical professionals, enabling it to assist in decision-making, improve outcomes, and streamline cancer care. These tools can help clinicians rule out potential cancer diagnoses based on symptoms and history, reducing unnecessary tests and consultations. Additionally, specialised LLMs can provide accessible, understandable information for patients while disseminating cutting-edge research to clinicians. Despite their potential, LLMs face notable limitations. Output quality varies based on the type of cancer or treatment, the specificity of questions, and phrasing. Many LLMs produce responses requiring advanced literacy, limiting accessibility. Moreover, AI bias remains a concern; training on biased data could perpetuate healthcare inequalities, leading to harmful recommendations. Accountability is another critical issue—the ability for LLMs to produce errors in its outputs raise questions about responsibility, highlighting the need for safeguards and clear frameworks to ensure equitable and reliable AI integration into cancer care.

癌症仍然是全球死亡的主要原因，但诊断和治疗癌症往往具有挑战性。诸如多次会诊、医疗系统负担过重以及初级卫生保健临床医生癌症特异性培训有限等障碍显著延迟了诊断并恶化了结果。为了应对这些挑战，卫生保健必须提高患者和临床医生的知识，同时尽量减少诊断和治疗延误。新兴技术，特别是人工智能（AI），通过改善诊断、教育和患者管理，有望彻底改变癌症治疗。像ChatGPT这样的大型语言模型（llm）在三个关键领域提供了令人兴奋的潜力：临床决策，患者教育和参与，以及获得肿瘤研究。研究表明，ChatGPT-4的肿瘤学相关性能接近医疗专业人员，使其能够协助决策，改善结果并简化癌症治疗。这些工具可以帮助临床医生根据症状和病史排除潜在的癌症诊断，减少不必要的检查和咨询。此外，专业法学硕士可以为患者提供可访问的，可理解的信息，同时向临床医生传播前沿研究。尽管法学硕士具有潜力，但也面临着明显的限制。输出的质量根据癌症或治疗的类型、问题的特异性和措辞而变化。许多法学硕士的回答需要高级的读写能力，限制了可访问性。此外，人工智能偏见仍然是一个问题；对有偏见的数据进行培训可能会使医疗不平等永久化，导致有害的建议。问责制是另一个关键问题——法学硕士在其产出中产生错误的能力引发了关于责任的问题，突出了保障措施和明确框架的必要性，以确保公平可靠地将人工智能整合到癌症治疗中。

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引用次数: 0