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*

Objective: To estimate the incidence of HIV-1 infection in men who have sex with men (MSM) in key areas of China through HIV-1 limiting antigen avidity enzyme immunoassay (LAg-Avidity EIA), analyze the deviation from the actual results and identify influencing factors, and provided reference for improving the accuracy of estimation results. Methods: Based on the principle of the cohort randomized study design, 20 cities were selected in China based on population size and the number of HIV-positive MSM. The sample size was estimated to be 700 according to the HIV-1 infection rate in MSM. MSM mobile phone app. was used to establish a detection appointment and questionnaire system, and the baseline cross-sectional survey was conducted from April to November 2019. LAg-Avidity EIA was used to identify the recent infected samples. The incidence of HIV-1 infection was calculated and then adjusted based on the estimation formula designed by WHO. The influencing factors were identified by analyzing the sample collection and detection processes. Results: Among the 10 650 blood samples from the participants, 799 were HIV-positive in initial screening, in which 198 samples (24.78%) missed during confirmation test. Only 621 samples were received by the laboratory. After excluding misreported samples, 520 samples were qualified for testing. A total of 155 samples were eventually determined as recent infection through LAg-Avidity EIA; Based on the estimation formula , the incidence of HIV-1 infection in MSM in 20 cities was 4.06% (95%CI:3.27%-4.85%), it increased to 5.53% (95%CI: 4.45%-6.60%)after the adjusting for sample missing rate. When the sample missing rate and misreporting rate were both adjusted, the incidence of HIV-1 infection in the MSM increased to 5.66% (95%CI:4.67%-6.65%). The actual incidence of HIV-1 infection in MSM in the 20 cities might be between 4.06% and 5.66%. Conclusions: Sample missing and misreporting might cause the deviation of the estimation of HIV-1 infection incidence. It is important to ensure the sample source and the quality of sample collection and detection to reduce the deviation in the estimation of HIV-1 infection incidence.
Cross-Sectional Studies ; HIV Infections/epidemiology* ; HIV-1 ; Homosexuality, Male ; Humans ; Immunoenzyme Techniques ; Incidence ; Male ; Sexual and Gender Minorities

Objective: To investigate the distribution of HIV-1 genetic subtypes and pretreatment drug resistance (PDR) among men who have sex with men (MSM) from 19 cities of 6 provinces in China. Methods: From April to November 2019, 574 plasma samples of ART-naive HIV-1 infected MSM were collected from 19 cities in Hebei, Shandong, Jiangsu, Zhejiang, Fujian, and Guangdong provinces, total ribonucleic acid (RNA) was extracted and amplified the HIV-1 pol gene region by nested polymerase chain reaction (PCR) after reverse transcription. Then sequences were used to construct a phylogenetic tree to determine genetic subtypes and submitted to the Stanford drug resistance database for drug resistance analysis. Results: A total of 479 samples were successfully amplified by PCR. The HIV-1 genetic subtypes included CRF01_AE, CRF07_BC, B, CRF55_01B, CRF59_01B, CRF65_cpx, CRF103_01B, CRF67_01B, CRF68_01B and unrecognized subtype, which accounted for 43.4%, 36.3%, 6.3%, 5.9%, 0.8%, 0.8%, 0.4%, 0.4%, 0.2% and 5.5%, respectively. The distribution of genetic subtypes among provinces is statistically different (χ²=44.141, P<0.001). The overall PDR rate was 4.6% (22/479), the drug resistance rate of non-nucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 3.5% (17/479), 0.8% (4/479) and 0.2% (1/479), respectively. The PDR rate of recent infections was significantly higher than that of long-term infections (χ²=4.634, P=0.031). Conclusions: The HIV-1 genetic subtypes among MSM infected with HIV-1 from 19 cities of 6 provinces in China are diverse, and the distribution of subtypes is different among provinces. The overall PDR rate is low, while the PDR rate of recent infections was significantly higher than that of long-term infections, suggesting the surveillance of PDR in recent infections should be strengthened.
China/epidemiology* ; Cities ; Drug Resistance ; Drug Resistance, Viral/genetics* ; Female ; Genotype ; HIV Infections/epidemiology* ; HIV Seropositivity/drug therapy* ; HIV-1/genetics* ; Homosexuality, Male ; Humans ; Male ; Phylogeny ; Reverse Transcriptase Inhibitors/therapeutic use* ; Sexual and Gender Minorities