Objective:To describe the hotspots and application trends of artificial intelligence (AI) in epidemiology in the past decade and analyze its advantages and challenges.Methods:The literatures with AI and epidemiology related keywords were systematically retrieved from Web of Science and China National Knowledge Infrastructure from 2014 to 2024. CiteSpace was used for bibliometric analysis of publication volume, keyword co-occurrence, clustering, emergence and cited literature co-occurrence analysis.Results:A total of 5 389 English papers and 1 659 Chinese papers were included, showing an increasing publication trend. High-frequency Chinese keywords included prediction, influencing factor, and machine learning, while English keywords frequently used were machine learning, prediction, and artificial intelligence. The Chinese keywords formed 14 clusters such as epidemiological characteristic, dietary pattern, and elderly individual, and the English keywords formed 21 clusters including prediction model, risk factor, and adult. In international studies, health policy, COVID-19, and digital health were the emerging frontier keywords. Eleven core papers were selected, covering key areas like traffic accident risk assessment, public health big data application, and deep learning in medical diagnosis.Conclusions:This study systematically summarized the research hotspots and development trends of AI applications in epidemiology over the past decade by using bibliometric methods, which indicated that current AI-based epidemiological studies are still in the exploratory phase, with the coexisting of both advantages and challenges. Continued attention should be paid to the future development of this field.

Objective:To investigate the indications for prenatal diagnosis using copy number variation-sequencing (CNV-seq) and the abnormalities detected by the method.Methods:This retrospective analysis involved 17 994 singleton pregnant women who underwent prenatal CNV-seq at the First Affiliated Hospital of Zhengzhou University from January 2019 to December 2022. These cases were divided into five groups based on the following indications for CNV-seq: abnormal fetal ultrasound findings, high-risk results indicated by non-invasive prenatal testing (NIPT) or Down's syndrome serological screening (Down's screening), adverse pregnancy history, and advanced maternal age. The proportions of cases with the indications for prenatal CNV-seq, the detection rates of abnormalities (numerical abnormalities of chromosomes, pathogenic/likely pathogenic CNV in structural abnormalities) in the five groups, and the distribution of these abnormalities were analyzed. Statistical analysis was performed using Chi-square test. Results:Among the 17 994 pregnant women, the women with abnormal fetal ultrasound findings, high-risk NIPT results, high-risk Down's screening results, adverse pregnancy history, and advanced maternal age accounted for 32.65% (5 875/17 994), 11.90% (2 142/17 994), 31.62% (5 690/17 994), 11.70% (2 105/17 994), and 12.13% (2 182/17 994), respectively. The detection rates of abnormalities in the five groups were 10.60% (623/5 875), 34.64% (742/2 142), 4.69% (267/5 690), 2.99% (63/2 105), and 3.67% (80/2 182), respectively. The overall detection rate of abnormalities was 9.86% (1 775/17 994). The cases with numerical abnormalities of chromosomes accounted for 68.79% (1 221/1 775), trisomy 21 was predominant (49.30%, 602/1 221). Chromosomal structural abnormalities were detected in 31.21% (554/1 775) of the cases with abnormalities, with 57.76% (320/554) harboring pathogenic CNVs and 42.24% (234/554) harboring likely pathogenic CNVs. The detection rate of chromosomal numerical abnormalities was higher than that of structural abnormalities in the abnormal fetal ultrasound group, NIPT high-risk group, and advanced maternal age group [6.81% (400/5 875) vs. 3.80% (223/5 875), χ2=53.10; 27.96% (599/2 142) vs. 6.68% (143/2 142), χ2=338.40; 2.43% (53/2 182) vs. 1.24% (27/2 182), χ2=8.61; all P<0.01]. A total of 416 microdeletions and 255 microduplications were detected in the 554 cases. The top three regions with the highest frequencies in microdeletions were Xp22.31 (12.74%, 53/416), 22q11.21 (7.93%, 33/416), and 17q12 (5.77%, 24/416); in microduplications, they were 22q11.21 (14.90%, 38/255), 17q12 (3.53%, 9/255), and 7q11.23 (3.53%, 9/255). Conclusions:Abnormal fetal ultrasound findings accounted for the highest proportion of prenatal diagnostic indications. The overall detection rate of abnormalities by CNV-seq is relatively high, especially in those with high-risk NIPT results as an indication for prenatal diagnosis. Among the chromosomal structural abnormalities detected in this study, the frequencies of Xp22.31 microdeletion and 22q11.21 microduplication are higher.

Objective:To develop an intelligent surveillance system for identifying upper gastrointestinal high-risk patients and assigning surveillance intervals, and to verify its efficacy.Methods:The endoscopic and pathological reports of 23 035 patients undergoing endoscopy at Renmin Hospital of Wuhan University from January to October 2021 were collected retrospectively. A training set of 17 934 patients (January to August) and a test set of 5 101 patients (September to October) were established. Keywords in the endoscopic and pathological reports were extracted by the intelligent surveillance system, and high-risk patients were automatically identified and classified into 7 risk levels. Then the standardized surveillance intervals were assigned based on the guideline. Guideline-based surveillance intervals assigned by expert endoscopists based on endoscopic and pathological reports were used as the golden standard. The accuracy of the intelligent surveillance system was calculated. Of the patients within the test set, 189 were hospitalized and the surveillance intervals given by physicians could be obtained from the electronic health records. The accuracy of the intelligent surveillance system with that of physicians from different departments was compared. Then 67 patients were randomly selected from 189 patients by simple random sampling to evaluate the adjunctive effect of the system in assigning surveillance intervals among 3 endoscopists.Results:The overall accuracy of the intelligent surveillance system in identifying upper gastrointestinal high-risk patients was 99.94% (5 098/5 101), and that of assigning surveillance intervals to correctly included patients was 100.00% (534/534). The intelligent surveillance system achieved significantly higher accuracy compared with all physicians from different departments [98.94% (187/189) VS 35.45% (67/189), χ2=118.01, P<0.001] as well as physicians from department of gastroenterology [100.00% (117/117) VS 24.79% (29/117), χ2=86.01, P<0.001]. With the assistance of the intelligent surveillance system, the endoscopists' accuracy of assigning surveillance intervals to 67 patients was significantly improved [55.22% (111/201) VS 22.39% (45/201), χ2=58.68, P<0.001]. Conclusion:The intelligent surveillance system can accurately identify upper gastrointestinal high-risk patients and assign surveillance intervals according to risk levels, which can alleviate the workload of doctors and improve the follow-up rate of patients.

Objective:To explore status and influencing factors of surveillance in colorectal post-polypectomy patients.Methods:Patients who underwent colorectal polypectomy in Renmin Hospital of Wuhan University between April 1, 2019 and June 30, 2019 were retrospectively studied. The surveillance information was obtained through electronic health record and telephone call. Status and influencing factors of surveillance in colorectal post-polypectomy patients were evaluated. Logistic regression model was used for multivariate analysis to determine independent risk factors influencing surveillance.Results:A total of 268 colorectal post-polypectomy patients and their surveillance information were reviewed, of whom 153 (57.09%) patients received surveillance colonoscopy, and 115 (42.91%) patients did not. Univariate analysis showed that the source of patients (outpatients VS inpatients, χ 2=5.68, P=0.017), department (others VS department of gastroenterology, χ 2=6.64, P=0.010), and the number of polyps (1/(2~4)/≥5, χ2=7.32, P=0.026) influenced the outcome of surveillance. Logistic regression model indicated that department of gastroenterology ( P=0.039, OR=2.12, 95% CI:1.04-4.34), risk level 3 ( P=0.040, OR=1.92, 95% CI:1.03-3.58) and the number of polyps ≥5 ( P=0.016, OR=2.89, 95% CI:1.22-6.83) were independent risk factors influencing surveillance. Conclusion:Patients visit the department of gastroenterology or had a risk level 3 or ≥5 polyps are more likely to opt for surveillance following the procedure.

Objective:To describe the hotspots and application trends of artificial intelligence (AI) in epidemiology in the past decade and analyze its advantages and challenges.Methods:The literatures with AI and epidemiology related keywords were systematically retrieved from Web of Science and China National Knowledge Infrastructure from 2014 to 2024. CiteSpace was used for bibliometric analysis of publication volume, keyword co-occurrence, clustering, emergence and cited literature co-occurrence analysis.Results:A total of 5 389 English papers and 1 659 Chinese papers were included, showing an increasing publication trend. High-frequency Chinese keywords included prediction, influencing factor, and machine learning, while English keywords frequently used were machine learning, prediction, and artificial intelligence. The Chinese keywords formed 14 clusters such as epidemiological characteristic, dietary pattern, and elderly individual, and the English keywords formed 21 clusters including prediction model, risk factor, and adult. In international studies, health policy, COVID-19, and digital health were the emerging frontier keywords. Eleven core papers were selected, covering key areas like traffic accident risk assessment, public health big data application, and deep learning in medical diagnosis.Conclusions:This study systematically summarized the research hotspots and development trends of AI applications in epidemiology over the past decade by using bibliometric methods, which indicated that current AI-based epidemiological studies are still in the exploratory phase, with the coexisting of both advantages and challenges. Continued attention should be paid to the future development of this field.

Objective:To investigate the indications for prenatal diagnosis using copy number variation-sequencing (CNV-seq) and the abnormalities detected by the method.Methods:This retrospective analysis involved 17 994 singleton pregnant women who underwent prenatal CNV-seq at the First Affiliated Hospital of Zhengzhou University from January 2019 to December 2022. These cases were divided into five groups based on the following indications for CNV-seq: abnormal fetal ultrasound findings, high-risk results indicated by non-invasive prenatal testing (NIPT) or Down's syndrome serological screening (Down's screening), adverse pregnancy history, and advanced maternal age. The proportions of cases with the indications for prenatal CNV-seq, the detection rates of abnormalities (numerical abnormalities of chromosomes, pathogenic/likely pathogenic CNV in structural abnormalities) in the five groups, and the distribution of these abnormalities were analyzed. Statistical analysis was performed using Chi-square test. Results:Among the 17 994 pregnant women, the women with abnormal fetal ultrasound findings, high-risk NIPT results, high-risk Down's screening results, adverse pregnancy history, and advanced maternal age accounted for 32.65% (5 875/17 994), 11.90% (2 142/17 994), 31.62% (5 690/17 994), 11.70% (2 105/17 994), and 12.13% (2 182/17 994), respectively. The detection rates of abnormalities in the five groups were 10.60% (623/5 875), 34.64% (742/2 142), 4.69% (267/5 690), 2.99% (63/2 105), and 3.67% (80/2 182), respectively. The overall detection rate of abnormalities was 9.86% (1 775/17 994). The cases with numerical abnormalities of chromosomes accounted for 68.79% (1 221/1 775), trisomy 21 was predominant (49.30%, 602/1 221). Chromosomal structural abnormalities were detected in 31.21% (554/1 775) of the cases with abnormalities, with 57.76% (320/554) harboring pathogenic CNVs and 42.24% (234/554) harboring likely pathogenic CNVs. The detection rate of chromosomal numerical abnormalities was higher than that of structural abnormalities in the abnormal fetal ultrasound group, NIPT high-risk group, and advanced maternal age group [6.81% (400/5 875) vs. 3.80% (223/5 875), χ2=53.10; 27.96% (599/2 142) vs. 6.68% (143/2 142), χ2=338.40; 2.43% (53/2 182) vs. 1.24% (27/2 182), χ2=8.61; all P<0.01]. A total of 416 microdeletions and 255 microduplications were detected in the 554 cases. The top three regions with the highest frequencies in microdeletions were Xp22.31 (12.74%, 53/416), 22q11.21 (7.93%, 33/416), and 17q12 (5.77%, 24/416); in microduplications, they were 22q11.21 (14.90%, 38/255), 17q12 (3.53%, 9/255), and 7q11.23 (3.53%, 9/255). Conclusions:Abnormal fetal ultrasound findings accounted for the highest proportion of prenatal diagnostic indications. The overall detection rate of abnormalities by CNV-seq is relatively high, especially in those with high-risk NIPT results as an indication for prenatal diagnosis. Among the chromosomal structural abnormalities detected in this study, the frequencies of Xp22.31 microdeletion and 22q11.21 microduplication are higher.

Objective:To develop an intelligent surveillance system for identifying upper gastrointestinal high-risk patients and assigning surveillance intervals, and to verify its efficacy.Methods:The endoscopic and pathological reports of 23 035 patients undergoing endoscopy at Renmin Hospital of Wuhan University from January to October 2021 were collected retrospectively. A training set of 17 934 patients (January to August) and a test set of 5 101 patients (September to October) were established. Keywords in the endoscopic and pathological reports were extracted by the intelligent surveillance system, and high-risk patients were automatically identified and classified into 7 risk levels. Then the standardized surveillance intervals were assigned based on the guideline. Guideline-based surveillance intervals assigned by expert endoscopists based on endoscopic and pathological reports were used as the golden standard. The accuracy of the intelligent surveillance system was calculated. Of the patients within the test set, 189 were hospitalized and the surveillance intervals given by physicians could be obtained from the electronic health records. The accuracy of the intelligent surveillance system with that of physicians from different departments was compared. Then 67 patients were randomly selected from 189 patients by simple random sampling to evaluate the adjunctive effect of the system in assigning surveillance intervals among 3 endoscopists.Results:The overall accuracy of the intelligent surveillance system in identifying upper gastrointestinal high-risk patients was 99.94% (5 098/5 101), and that of assigning surveillance intervals to correctly included patients was 100.00% (534/534). The intelligent surveillance system achieved significantly higher accuracy compared with all physicians from different departments [98.94% (187/189) VS 35.45% (67/189), χ2=118.01, P<0.001] as well as physicians from department of gastroenterology [100.00% (117/117) VS 24.79% (29/117), χ2=86.01, P<0.001]. With the assistance of the intelligent surveillance system, the endoscopists' accuracy of assigning surveillance intervals to 67 patients was significantly improved [55.22% (111/201) VS 22.39% (45/201), χ2=58.68, P<0.001]. Conclusion:The intelligent surveillance system can accurately identify upper gastrointestinal high-risk patients and assign surveillance intervals according to risk levels, which can alleviate the workload of doctors and improve the follow-up rate of patients.

Objective:To explore status and influencing factors of surveillance in colorectal post-polypectomy patients.Methods:Patients who underwent colorectal polypectomy in Renmin Hospital of Wuhan University between April 1, 2019 and June 30, 2019 were retrospectively studied. The surveillance information was obtained through electronic health record and telephone call. Status and influencing factors of surveillance in colorectal post-polypectomy patients were evaluated. Logistic regression model was used for multivariate analysis to determine independent risk factors influencing surveillance.Results:A total of 268 colorectal post-polypectomy patients and their surveillance information were reviewed, of whom 153 (57.09%) patients received surveillance colonoscopy, and 115 (42.91%) patients did not. Univariate analysis showed that the source of patients (outpatients VS inpatients, χ 2=5.68, P=0.017), department (others VS department of gastroenterology, χ 2=6.64, P=0.010), and the number of polyps (1/(2~4)/≥5, χ2=7.32, P=0.026) influenced the outcome of surveillance. Logistic regression model indicated that department of gastroenterology ( P=0.039, OR=2.12, 95% CI:1.04-4.34), risk level 3 ( P=0.040, OR=1.92, 95% CI:1.03-3.58) and the number of polyps ≥5 ( P=0.016, OR=2.89, 95% CI:1.22-6.83) were independent risk factors influencing surveillance. Conclusion:Patients visit the department of gastroenterology or had a risk level 3 or ≥5 polyps are more likely to opt for surveillance following the procedure.

Objective To conduct bibliometric visualization analyses of the literature domestic and overseas on active surveillance of post-marketing safety of drugs,aiming to display the current status and trend of hotspots in this field and to provide references for future research and the improvement of the Chinese management system of active surveillance.Methods The English and Chinese literature on active surveillance of post-marketing safety of drugs were searched in Web of Science and CNKI respectively and imported into CiteSpace 6.3.R2 software for the analysis of the number of publications,authors,institutions,and national cooperative networks,and the analysis of keyword co-occurrence,clustering and emergence.Results 415 Chinese and 676 English literature were included,with an overall increasing trend in annual publication volume.The author collaboration network of Chinese literature was smaller than that of English literature,and the partnership network was sparse,with no strong centralized institution.Domestic drug regulatory agencies played an important role in the field,while drug companies'monitoring research on their own products was still relatively scarce.The research topic covered active surveillance systems,technical method research,and drug safety active surveillance practice research for specific drugs and diseases.Conclusion Countries worldwide have widely considered active surveillance of post-marketing drug safety.The heat of research activities in China has shown a significant growth trend.However,there is still a significant gap compared with the international frontiers.Further cooperation needs to be strengthened to promote the improvement of the active surveillance management system in China.

Objective:To explore the genetic basis for a Chinese pedigree affected with Fragile X syndrome (FXS) through Nanopore long-read sequencing.Methods:A FXS pedigree who had undergone genetic counseling at the First Affiliated Hospital of Zhengzhou University in April 2023 was selected as the study subject. Nanopore long-read sequencing, triplet-repeat primed PCR (TP-PCR), methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) and trinucleotide polymorphism genotyping of androgen receptor (AR) gene were used to analyze the FMR1 CGG repeat number, methylation, and X chromosome inactivation of the pedigree members. This study has been approved by the Medical Ethics Committee of the First Affiliated Hospital of Zhengzhou University (No. KS-2018-KY-36). Results:Full mutation and CpG island hypermethylation were detected in the proband. The elder sister of the proband had full mutation of the FMR1 gene on one X chromosome and hypermethylation of CpG island, while the FMR1 gene on the other X chromosome was normal. FMR1 premutation was detected in the proband′s mother. Conclusion:Nanopore long-read sequencing can simultaneously detect the dynamic mutation and methylation status of the FMR1 gene on the two X chromosomes of females, which has important value for the diagnosis of FXS in different genders.