As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

As of Apr. 22, 2020, the World Health Organization (2020) has reported over 2.4 million confirmed coronavirus disease 2019 (COVID-19) patients and 169 151 deaths. Recent articles have uncovered genomic characteristics and clinical features of COVID-19 (Chan et al., 2020; Chang et al., 2020; Guan et al., 2020; Zhu et al., 2020), while our understanding of COVID-19 is still limited. As suggested by guidelines promoted by the General Office of National Health Commission of the People's Republic of China (2020) (from Versions 1 to 6), discharged standards for COVID-19 were still dependent on viral real-time polymerase chain reaction (RT-PCR) tests of respiratory specimens, showing that recovered COVID-19 patients with twice negative RT-PCR could meet discharge criteria. Here, we examined two cases in which nucleic acid test results were inconsistent with clinical and radiological findings, leading to suboptimal care.
Adult ; Betacoronavirus ; China ; Clinical Laboratory Techniques ; Coronavirus Infections ; diagnosis ; transmission ; Female ; Humans ; Male ; Middle Aged ; Pandemics ; Patient Discharge ; Pneumonia, Viral ; diagnosis ; transmission ; Real-Time Polymerase Chain Reaction ; Reverse Transcriptase Polymerase Chain Reaction ; Sputum ; virology

The recently emerged novel coronavirus pneumonia, named the coronavirus disease 2019 (COVID-19), shares several clinical characteristics with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), and spread rapidly throughout China in December of 2019 (Huang et al., 2020). The pathogen 2019 novel coronavirus (2019-nCoV) is now named SARS coronavirus 2 (SARS-CoV-2) and is highly infectious. As of Apr. 9, 2020, over 80 000 confirmed cases had been reported, with an estimated mortality rate of 4.0% (Chinese Center for Disease Control and Prevention, 2020). Person-to-person transmission and familial clustering have been reported (Chan et al., 2020; Nishiura et al., 2020; Phan et al., 2020). However, there is no evidence of fetal intrauterine infection in pregnant women who have been infected with SARS-CoV-2 in their third trimester (Chen et al., 2020). It is unclear whether breastfeeding transmits the virus from previously infected and recovered mothers to their babies. Here we report the clinical course of a pregnant woman with COVID-19. In order to determine whether SARS-CoV-2 can be transmitted to newborns through breastfeeding, we measured viral RNA in the patient's breastmilk samples at different time points after delivery.
Adult ; Betacoronavirus ; Breast Feeding ; China ; Coronavirus Infections ; diagnosis ; Female ; Humans ; Infant, Newborn ; Infectious Disease Transmission, Vertical ; Milk, Human ; virology ; Pandemics ; Pneumonia, Viral ; diagnosis ; Pregnancy ; Pregnancy Complications, Infectious ; virology ; RNA, Viral ; isolation & purification