Abstract Background In the translation of traditional Chinese medicine (TCM), it is crucial to preserve the authenticity of its philosophical, historical, and linguistic characteristics. This study aims to conduct a comprehensive analysis of translation strategies for adapting TCM terminology to foreign cultural contexts, based on the classical text The Emperor”s Canon of Eighty-One Difficult Issues. Methods A comparative analysis was performed to evaluate the effectiveness of foreignization and domestication strategies in translating TCM terminology into Russian, using an experimental study involving 84 respondents (42 in each group). The Student’s t-test was employed to assess medical accuracy, equivalence, pragmatic value, terminological precision, and cultural specificity. Results The results revealed a statistically significant advantage of the domestication strategy across most metrics, particularly in equivalence (p = 0.001) and pragmatic value (p = 0.008), where domestication achieved higher mean scores (4.12 and 4.03) compared to foreignization (3.48 and 3.55). Thus, it was established that domestication facilitates better adaptation of complex Chinese medical concepts for target audiences while maintaining sufficient medical accuracy. This is supported by higher scores in overcoming cultural barriers (48.8% versus 22.0%) and ensuring terminological precision (3.88 versus 3.41), making it a more effective strategy for translating medical terminology from Chinese into Russian. Conclusions The practical significance of this study lies in determining the effectiveness of translation approaches for TCM terminology into Russian through experimental research. These findings can be applied in the work of medical translators, the development of educational materials on Chinese medicine, and the creation of methodological guidelines for medical text translation. Consequently, the results hold the potential to improve the quality of educational materials on TCM and enhance intercultural medical communication.
Since the implementation of the new healthcare reforms, China's healthcare industry has achieved significant development. However, pressing issues such as bypassing primary care for specialist visits, preference for high-level medical resources, passive health awareness, and doctor-patient conflicts remain severe. These problems may be attributed to the lag in the construction of residents' healthcare-seeking culture. This paper provides an in-depth analysis of the concept, structural dimensions, and value functions of healthcare-seeking culture. From the dual perspectives of healthcare value cognition and healthcare-seeking cultural choices, it elucidates the profound impact of healthcare-seeking culture on residents' medical behaviors and the order of healthcare-seeking activities. Addressing the current confusion in residents' healthcare-seeking culture, the paper proposes practical approaches, including implementing a hierarchical diagnosis and treatment system, enhancing public education on healthcare culture, fostering harmonious doctor-patient relationships, and optimizing the allocation of medical resources. The aim is to promote the scientific and rational transformation of residents' healthcare-seeking culture, provide new references for regulating social healthcare-seeking order, enhancing public health outcomes, and supporting the implementation of the Healthy China strategy.
Reexamining science journalism through the constructivist lens of Science and Technology Studies (STS), the present paper argues that this perspective promotes a more responsible approach to reporting scientific discoveries in medicine. The dominant anti-constructivist, realist approach often results in what we term "dramatic modalization," which attributes greater facticity and universality to scientific findings than they actually possess at the time of publication, leading to significant moral consequences.To illustrate this, we will first explore the STS perspective as a framework for understanding the construction of facts in practice. Next, through a discourse analysis of two historical cases in medical journalism—the MMR-autism link and the depression-serotonin connection—we will demonstrate that the realist media coverage of these cases engaged in dramatic modalization, resulting in tangible moral repercussions. We hereby propose an alternative STS model for science journalism in medicine, arguing that it offers a more morally responsible approach.
History of medicine. Medical expeditions, Medical philosophy. Medical ethics
Vision-language foundation models (VLMs) have shown great potential in feature transfer and generalization across a wide spectrum of medical-related downstream tasks. However, fine-tuning these models is resource-intensive due to their large number of parameters. Prompt tuning has emerged as a viable solution to mitigate memory usage and reduce training time while maintaining competitive performance. Nevertheless, the challenge is that existing prompt tuning methods cannot precisely distinguish different kinds of medical concepts, which miss essentially specific disease-related features across various medical imaging modalities in medical image classification tasks. We find that Large Language Models (LLMs), trained on extensive text corpora, are particularly adept at providing this specialized medical knowledge. Motivated by this, we propose incorporating LLMs into the prompt tuning process. Specifically, we introduce the CILMP, Conditional Intervention of Large Language Models for Prompt Tuning, a method that bridges LLMs and VLMs to facilitate the transfer of medical knowledge into VLM prompts. CILMP extracts disease-specific representations from LLMs, intervenes within a low-rank linear subspace, and utilizes them to create disease-specific prompts. Additionally, a conditional mechanism is incorporated to condition the intervention process on each individual medical image, generating instance-adaptive prompts and thus enhancing adaptability. Extensive experiments across diverse medical image datasets demonstrate that CILMP consistently outperforms state-of-the-art prompt tuning methods, demonstrating its effectiveness. Code is available at https://github.com/usr922/cilmp.
Abstract Background The swift advancement of intensive care medicine, coupled with technological possibilities, has prompted numerous ethical inquiries regarding decision-making processes concerning the withholding or withdrawal of treatment due to medical futility. This study seeks to delineate the decision-making approaches employed by intensive care physicians in Türkiye when faced with medical futility at the end of life, along with an ethical evaluation of these practices. Methods Grounded theory, a qualitative analysis method was employed, conducting semi-structured, in-depth interviews with eleven intensive care physicians in Türkiye. The subsequent text analysis was carried out using MAXQDA software. Results Participants assert that the decisions made by Turkish physicians determine whether treatment is futile, rely on medical consensus, and lack a standardized decision-making process. The decisions are influenced by legal and social pressures, resource constraints, and occasional conflicts of interest. The significance of professional hierarchy is notable, with limited consideration given to the opinions of nurses and other staff. The unstructured medical consensus processes are shaped by normative concepts such as benefit, age, justice, and conscience. Furthermore, it was observed that the conscientious opinions of physicians carry more weight than adherence to ethical principles and guidelines. Conclusion To create optimal conditions for doctors to make ethically justifiable decisions, the dynamics within the treatment team should be improved, emphasizing the minimization of hierarchy, and ensuring the active participation of all team members in the decision-making process. Additionally, efforts should be directed toward narrowing the gap between the conscience of the individual doctor and established ethical principles. A potential solution lies in the nationwide implementation of clinical ethics committees and the establishing of clinical ethics guidelines, aiming to address, and overcome the identified challenges.
En el presente trabajo se analiza la posibilidad de teorizar una neuroética de la mentira. Para hablar de una neuroética de la mentira su definición debería ser clara y exacta. En este estudio sostengo que no es así, la mentira no está bien definida y la neurociencia no logra crear una teoría de la mentira sólida. Finalmente se proponen una serie de puntos que permitan construir una neuroética de la mentira.
Jurisprudence. Philosophy and theory of law, Medical philosophy. Medical ethics
Abstract Background The existence of a valid instrument to evaluate the attitude of mothers towards compliance with medical ethics during childbirth can lead to appropriate interventions to create a positive attitude. The purpose of this study is to determine the construct validity of the MEAVDQ (Medical Ethics Attitude in Vaginal Delivery Questionnaire). Methods The study was carried out with 350 women. The main research instrument was MEAVDQ. This 59-item questionnaire comprises three parts A, B, J. Part A is concerned with the first principles. Part B deals with the second and third principles and part J addresses the fourth principle of medical ethics. Structural Equations Modeling (SEM) was used to determine the construct validity of MEAVDQ. Results The results of SEM revealed that there was a positive correlation between structures A and B. The relationship between structures B and J was also positive and significant. On the other hand, there was a direct and indirect relationship between structures A and J. One-unit increase in structure A led to 0.16 (95% CI: 0.01, 0.33) direct increase in structure J. Also, one-unit increase score increases in structure A caused 0.39 indirect rise (95% CI: 0.26, 0.53) in structure J with the mediating role of the structure B. Conclusions It can be suggested to midwifery policy maker and midwives that respect for the first principle of medical ethics and autonomy is the most important principle of medical ethics in childbirth. By respecting the autonomy of mothers, a positive birth experience can be created for them.
Mary Kimani, Sassy Molyneux, Anderson Charo
et al.
Abstract Background Carefully planned research is critical to developing policies and interventions that counter physical, psychological and social challenges faced by young people living with HIV/AIDS, without increasing burdens. Such studies, however, must navigate a ‘vulnerability paradox’, since including potentially vulnerable groups also risks unintentionally worsening their situation. Through embedded social science research, linked to a cohort study involving Adolescents Living with HIV/AIDS (ALH) in Kenya, we develop an account of researchers’ responsibilities towards young people, incorporating concepts of vulnerability, resilience, and agency as ‘interacting layers’. Methods Using a qualitative, iterative approach across three linked data collection phases including interviews, group discussions, observations and a participatory workshop, we explored stakeholders’ perspectives on vulnerability and resilience of young people living with HIV/AIDS, in relation to home and community, school, health care and health research participation. A total of 62 policy, provider, research, and community-based stakeholders were involved, including 27 ALH participating in a longitudinal cohort study. Data analysis drew on a Framework Analysis approach; ethical analysis adapts Luna’s layered account of vulnerability. Results ALH experienced forms of vulnerability and resilience in their daily lives in which socioeconomic context, institutional policies, organisational systems and interpersonal relations were key, interrelated influences. Anticipated and experienced forms of stigma and discrimination in schools, health clinics and communities were linked to actions undermining ART adherence, worsening physical and mental health, and poor educational outcomes, indicating cascading forms of vulnerability, resulting in worsened vulnerabilities. Positive inputs within and across sectors could build resilience, improve outcomes, and support positive research experiences. Conclusions The most serious forms of vulnerability faced by ALH in the cohort study were related to structural, inter-sectoral influences, unrelated to study participation and underscored by constraints to their agency. Vulnerabilities, including cascading forms, were potentially responsive to policy-based and interpersonal actions. Stakeholder engagement supported cohort design and implementation, building privacy, stakeholder understanding, interpersonal relations and ancillary care policies. Structural forms of vulnerability underscore researchers’ responsibilities to work within multi-sectoral partnerships to plan and implement studies involving ALH, share findings in a timely way and contribute to policies addressing known causes of vulnerabilities.
Abstract Background While the number of emergency patients worldwide continues to increase, emergency doctors often face moral distress. It hampers the overall efficiency of the emergency department, even leading to a reduction in human resources. Aim This study explored the experience of moral distress among emergency department doctors and analyzed the causes of its occurrence and the strategies for addressing it. Method Purposive and snowball sampling strategies were used in this study. Data were collected through in-depth, semi-structured interviews with 10 doctors working in the emergency department of a tertiary general hospital in southwest China. The interview data underwent processing using the Nvivo 14 software. The data analysis was guided by Colaizzi’s phenomenological analysis method. Study findings This study yielded five themes: (1) imbalance between Limited Medical Resources and High-Quality Treatment Needs; (2) Ineffective Communication with Patients; (3) Rescuing Patients With no prospect of treatment; (4) Challenges in Sustaining Optimal Treatment Measures; and (5) Strategies for Addressing Moral Distress. Conclusion The moral distress faced by emergency doctors stems from various aspects. Clinical management and policymakers can alleviate this distress by enhancing the dissemination of emergency medical knowledge to the general public, improving the social and economic support systems, and strengthening multidisciplinary collaboration and doctors’ communication skills.
Interpretability is often an essential requirement in medical imaging. Advanced deep learning methods are required to address this need for explainability and high performance. In this work, we investigate whether additional information available during the training process can be used to create an understandable and powerful model. We propose an innovative solution called Proto-Caps that leverages the benefits of capsule networks, prototype learning and the use of privileged information. Evaluating the proposed solution on the LIDC-IDRI dataset shows that it combines increased interpretability with above state-of-the-art prediction performance. Compared to the explainable baseline model, our method achieves more than 6 % higher accuracy in predicting both malignancy (93.0 %) and mean characteristic features of lung nodules. Simultaneously, the model provides case-based reasoning with prototype representations that allow visual validation of radiologist-defined attributes.
Heather M. Whitney, Natalie Baughan, Kyle J. Myers
et al.
Purpose: The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary imaging dataset compared to the United States general population (US Census) and COVID-19 positive case counts from the Centers for Disease Control and Prevention (CDC). Approach: The Jensen Shannon distance (JSD) was used to longitudinally measure the similarity of the distribution of (1) all unique patients in the MIDRC data to the 2020 US Census and (2) all unique COVID-19 positive patients in the MIDRC data to the case counts reported by the CDC. The distributions were evaluated in the demographic categories of age at index, sex, race, ethnicity, and the intersection of race and ethnicity. Results: Representativeness the MIDRC data by ethnicity and the intersection of race and ethnicity was impacted by the percentage of CDC case counts for which data in these categories is not reported. The distributions by sex and race have retained their level of representativeness over time. Conclusion: The representativeness of the open medical imaging datasets in the curated public data commons at MIDRC has evolved over time as both the number of contributing institutions and overall number of subjects has grown. The use of metrics such as the JSD support measurement of representativeness, one step needed for fair and generalizable AI algorithm development.
The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-based interface. However, recent studies and individual experiments have shown that SAM underperforms in medical image segmentation, since the lack of the medical specific knowledge. This raises the question of how to enhance SAM's segmentation capability for medical images. In this paper, instead of fine-tuning the SAM model, we propose the Medical SAM Adapter (Med-SA), which incorporates domain-specific medical knowledge into the segmentation model using a light yet effective adaptation technique. In Med-SA, we propose Space-Depth Transpose (SD-Trans) to adapt 2D SAM to 3D medical images and Hyper-Prompting Adapter (HyP-Adpt) to achieve prompt-conditioned adaptation. We conduct comprehensive evaluation experiments on 17 medical image segmentation tasks across various image modalities. Med-SA outperforms several state-of-the-art (SOTA) medical image segmentation methods, while updating only 2\% of the parameters. Our code is released at https://github.com/KidsWithTokens/Medical-SAM-Adapter.
Deep learning has achieved widespread success in medical image analysis, leading to an increasing demand for large-scale expert-annotated medical image datasets. Yet, the high cost of annotating medical images severely hampers the development of deep learning in this field. To reduce annotation costs, active learning aims to select the most informative samples for annotation and train high-performance models with as few labeled samples as possible. In this survey, we review the core methods of active learning, including the evaluation of informativeness and sampling strategy. For the first time, we provide a detailed summary of the integration of active learning with other label-efficient techniques, such as semi-supervised, self-supervised learning, and so on. We also summarize active learning works that are specifically tailored to medical image analysis. Additionally, we conduct a thorough comparative analysis of the performance of different AL methods in medical image analysis with experiments. In the end, we offer our perspectives on the future trends and challenges of active learning and its applications in medical image analysis.
Abstract Background Following the increased presence of the Right-to-Die Movement, improved end-of-life options, and the political and legal status of aid-in-dying around the globe, suicide tourism has become a promising alternative for individuals who wish to end their lives. Yet, little is known about this from the perspective of those who engage in the phenomenon. Methods This study applied the qualitative research approach, following the grounded theory tradition. It includes 11 in-depth semi-structured interviews with Israeli members of the Swiss non-profit Dignitas who contemplated traveling to Switzerland for aid-in-dying. Results Seven themes emerged from the data analysis, including health and functioning; feelings regarding survivorship and existence; interacting with the health sector; attitudes regarding death and dying; suicide; choosing death; and choosing suicide tourism. A significant portion of the participants had experienced suicidal thoughts and had even previously attempted suicide, some more than once. Most of them referred to chronic illnesses, functional disability, and social isolation. They understand suffering within the subjective dimension, namely only by the person who is actually subjected to the disease, ailments, and disability. Participants regarded aid-in-dying in Switzerland as positive thanks to its guaranteed outcome: "beautiful death", compared to "disadvantaged dying" which places a burden on the participants' loved ones throughout the prolonged dying. Most of them do not necessarily want to have their loved ones beside them when they die, and they see no significant meaning in dying in a foreign country to which they have no emotional or civil attachment. Conclusion The desirable approval or tragic refusal by Dignitas to participants' requests for suicide tourism enhances the paradox between the perception of aid-in-dying as a mechanism for fulfilling controlled death and its bureaucratic and materialistic characteristics specifically reflected in a paid, formalized approach to aid-in-dying that cultivate dependency and collaboration.
Ana Cristina Vidigal Soeiro Ana Soeiro, Victor de Souza Vasconcelos, Thalita da Rocha Bastos
A humanização vem ganhando ampla repercussão no campo da ética médica, apontando a importância dos Cuidados Paliativos e da sedação paliativa quando a morte se revela uma imponderável realidade. O artigo visa estimular a reflexão bioética sobre a sedação paliativa, considerando as discussões contemporâneas sobre o morrer com dignidade. Trata-se de um estudo exploratório e descritivo, com participação de médicos/as de um hospital oncológico. Os achados demonstram que a sedação paliativa auxilia o manejo da dor e do sofrimento, entretanto, é necessária a intensificação das discussões sobre o tema, incluindo maior participação de pacientes nas decisões médicas.
Medical philosophy. Medical ethics, Business ethics
Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten
Reliably and physically accurately transferring information between images through deformable image registration with large anatomical differences is an open challenge in medical image analysis. Most existing methods have two key shortcomings: first, they require extensive up-front parameter tuning to each specific registration problem, and second, they have difficulty capturing large deformations and content mismatches between images. There have however been developments that have laid the foundation for potential solutions to both shortcomings. Towards the first shortcoming, a multi-objective optimization approach using the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (RV-GOMEA) has been shown to be capable of producing a diverse set of registrations for 2D images in one run of the algorithm, representing different trade-offs between conflicting objectives in the registration problem. This allows the user to select a registration afterwards and removes the need for up-front tuning. Towards the second shortcoming, a dual-dynamic grid transformation model has proven effective at capturing large differences in 2D images. These two developments have recently been accelerated through GPU parallelization, delivering large speed-ups. Based on this accelerated version, it is now possible to extend the approach to 3D images. Concordantly, this work introduces the first method for multi-objective 3D deformable image registration, using a 3D dual-dynamic grid transformation model based on simplex meshes while still supporting the incorporation of annotated guidance information and multi-resolution schemes. Our proof-of-concept prototype shows promising results on synthetic and clinical 3D registration problems, forming the foundation for a new, insightful method that can include bio-mechanical properties in the registration.
AbstractThe traditional structure of medical school curriculum in the United States consists of 2 years of pre-clinical study followed by 2 years of clinical rotations. In this essay, I propose that this curricular approach stems from the understanding that medicine is both a science, or a body of knowledge, as well as an art, or a craft that is practiced. I then argue that this distinction between science and art is also relevant to the field of medical ethics, and that this should be reflected in ethics curriculum in medical education. I introduce and argue for virtue ethics as the best opportunity for introducing practical ethical knowledge to medical trainees.