Background Respect for patients’ autonomy is usually considered to be an important ethical principle in Western countries; privacy is one of the implications of such respect. Healthcare professionals frequently encounter ethical dilemmas during their practice. The past few decades have seen an increased use of courts to resolve intractable ethical dilemmas across both the developed and the developing world. However, Chinese and American bioethics differ largely due to the influence of Chinese Confucianism and Western religions, respectively, and there is a (...) dearth of comparative studies that explore cases of ethical dilemmas between China and the United States. Methods This paper discusses four typical cases with significant social impact. First, it compares two cases concerning patient privacy: the “Shihezi University Hospital Case”, in which a patient was used as a clinical teaching object without her permission, and the “New York-Presbyterian Hospital Case”, in which the hospital allowed the filming of a patient’s treatment without his consent. Second, it compares two cases regarding patient autonomy and potentially life-saving medical procedures: the “Case of Ms. L”, concerning a cohabitant’s refusal to sign a consent form for a pregnant woman’s caesarean, and the “Case of Mrs. V”, concerning a hospital’s insistence upon a blood transfusion for a dissenting patient. This paper introduces the supporting and opposing views for each case and discusses their social impact. It then compares and analyses the differences between China and the United States from cultural and legislative perspectives. Conclusions Ethical dilemmas have often occurred in China due to the late development of bioethics. However, the presence of bioethics earlier in the US than in China has not spared the US of ethical dilemmas. This paper highlights lessons and inspiration from the cases for healthcare professionals and introduces readers to the role and weight of privacy and autonomy in China and in the US from the perspectives of different cultures, religions and laws. (shrink)

The target article describes a Dutch case that happened in 2008, where Albert Heringa helped his 98-year-old mother, whose general practitioner rejected her request for an assisted d...

Ankeny et al. focuses on the recent creation of “iBlastoids” and defends the need for reflexive, anticipatory, and deliberative approaches in the domain of emerging and potentially contentio...

The target article by Laacke et al. focuses on the specific context of identifying people in social media with a high risk of depression by using artificial intelligence technologies. I...

The target article by David Alfandre et al. offers a new ethical framework to guide COVID-19 contingency surge planning and response, and applies this ethical framework to three case example...

Svirsky, Howard, and Berman have enumerated a variety of U.S. FDA roles, arguing that although the public possess a “right to information” about health risks,...

In “Deception and the Clinical Ethicist,” Meyers defends the argument that the clinical ethicist should sometimes be an active participant in the deception of patients and their families. Me...

Legal Judgment Summarization (LJS) can highly summarize legal judgment documents, improving judicial work efficiency in case retrieval and other occasions. Legal judgment documents are usually lengthy; however, most existing LJS methods are directly based on general text summarization models, which cannot handle long texts effectively. Additionally, due to the complex structural characteristics of legal judgment documents, some information may be lost by applying only one single kind of summarization model. To address these issues, we propose an integrated summarization method which (...) leverages both semantic and structural information to improve the quality of LJS. Specifically, legal judgment documents are firstly segmented into three relatively short parts according to their specific structure. We propose an extractive summarization model named BSLT and an abstractive summarization model named LPGN by adopting Lawformer as the encoder. Lawformer is a new pre-trained language model for long legal documents, which specializes in capturing long-distance dependency and modeling legal semantic features. Then, we adopt different models to summarize the corresponding part regarding its structural characteristics. Finally, the obtained summaries are integrated to generate a high-quality summary involving semantic and structural information. We conduct comparative experiments to evaluate the performance of our model. The results show that our model outperforms the baseline model LEAD-3 by 14.78% on the mean ROUGE score, which demonstrates our method is effective in LJS and is prospected to be applied to assist other tasks in legal artificial intelligence. (shrink)

Similar case analysis (SCA) is an essential topic in legal artificial intelligence, serving as a reference for legal professionals. Most existing works treat SCA as a traditional text classification task and ignore some important legal elements that affect the verdict and case similarity, like legal events, and thus are easily misled by semantic structure. To address this issue, we propose a Legal Event-Context Model named LECM to improve the accuracy and interpretability of SCA based on Chinese legal corpus. The event-context (...) integration mechanism, which is an essential component of the LECM, is proposed to integrate the legal event and context information based on the attention mechanism, enabling legal events to be associated with their corresponding relevant contexts. We introduce an event detection module to obtain the legal event information, which is pre-trained on a legal event detection dataset to avoid labeling events manually. We conduct extensive experiments on two SCA tasks, i.e., similar case matching (SCM) and similar case retrieval (SCR). Compared with baseline models, LECM is validated by about 13% and 11% average improvement in terms of mean average precision and accuracy respectively, for SCR and SCM tasks. These results indicate that LECM effectively utilizes event-context knowledge to enhance SCA performance and its potential application in various legal document analysis tasks. (shrink)

In the target article by Kolbe and de Melo-Martin (2023), the authors discussed several shortcomings of major instruments of moral distress, including the Moral Distress Scale (MDS) (Corley et al....

The target article (Nelson et al. 2023) offers a valuable contribution to the “paradox of experience,” which was illustrated by using examples about access to unproven medical products and disabili...

With the rapid development of science and technology, UAVs have become a new type of weapon in the informatization battlefield by their advantages of low loss and zero casualty rate. In recent years, UAV navigation electromagnetic decoy and electromagnetic interference crashes have activated widespread international attention. The UAV LiDAR detection system is susceptible to electromagnetic interference in a complex electromagnetic environment, which results in inaccurate detection and causes the mission to fail. Therefore, it is very necessary to predict the effects (...) of the electromagnetic environment. Traditional electromagnetic environment effect prediction methods mostly use a single model of mathematical model and machine learning, but the traditional prediction method has poor processing nonlinear ability and weak generalization ability. Therefore, this paper uses the Stacking fusion model algorithm in machine learning to study the electromagnetic environment effect prediction. This paper proposes a Stacking fusion model based on machine learning to predict electromagnetic environment effects. The method consists of Extreme Gradient Boosting algorithm, Gradient Boosting Decision Tree algorithm, K Nearest Neighbor algorithm, and Decision Tree algorithm. Experimental results show that, comprising with the other seven machine learning algorithms, the Stacking fusion model has a better classification prediction accuracy of 0.9762, a lower Hamming code distance of 0.0336, and a higher Kappa coefficient of 0.955. The fusion model proposed in this paper has a better predictive effect on electromagnetic environment effects and is of great significance for improving the accuracy and safety of UAV LiDAR detection systems under the complex electromagnetic environment on the battlefield. (shrink)

Mass media play a significant role in shaping public opinion. News coverage of abortion reflects narratives about reproductive health, ethics, and women, and may potentially reinforce negative soci...

Bowman-Smart et al. (2023) sketched a hypothetical scenario involving noninvasive prenatal testing (NIPT) for “non-medical” traits available for expectant parents in the near future. By critically...

The target article by Lynch et al. offers approaches for improving trial availability and Expanded Access for non-pandemic diseases based on the analysis of the COVID-19 experience in the US...