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Deng ZH, Tan HJ, Wang L, Long PP, Guo D, Quan RP, Zeng MH, Deng HW, Xiao HM. A bibliometric analysis of primary ovarian insufficiency from 2010 to 2020. Climacteric 2022; 25:497-503. [PMID: 35373679 DOI: 10.1080/13697137.2022.2052841] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE This study aimed to carry out a bibliometric analysis of primary ovarian insufficiency (POI) from 2010 to 2020 and to reveal the research status and hotspots in the future. METHOD A total of 3087 articles and reviews related to POI published from 2010 to 2020 retrieved from the Web of Science Core Collection were used for bibliometric analysis. CiteSpace and VOSviewer were adopted to analyze countries and regions, organizations, authors, journals, keywords and co-cited references. RESULTS The number of publications about POI increased year by year. The USA produced the largest number of publications and the most influence in this field. The main research directions of POI can be roughly divided into four aspects according to the analysis of keywords and co-cited references: genetic research of POI; stem cell therapy for patients with POI; prediction of ovarian function; and fertility preservation of cancer patients. Genetic research and stem cell therapy may become research hotspots in the future. CONCLUSION This study might be the first bibliometric study to analyze publications of POI from multiple indicators, in order to provide new opinions for the research trends and possible hotspots of POI.
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Affiliation(s)
- Z-H Deng
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - H-J Tan
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - L Wang
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - P-P Long
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - D Guo
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - R-P Quan
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - M-H Zeng
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - H-W Deng
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - H-M Xiao
- Institute of Reproductive & Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
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Wang KS, Yu G, Xu C, Meng XH, Zhou J, Zheng C, Deng Z, Shang L, Liu R, Su S, Zhou X, Li Q, Li J, Wang J, Ma K, Qi J, Hu Z, Tang P, Deng J, Qiu X, Li BY, Shen WD, Quan RP, Yang JT, Huang LY, Xiao Y, Yang ZC, Li Z, Wang SC, Ren H, Liang C, Guo W, Li Y, Xiao H, Gu Y, Yun JP, Huang D, Song Z, Fan X, Chen L, Yan X, Li Z, Huang ZC, Huang J, Luttrell J, Zhang CY, Zhou W, Zhang K, Yi C, Wu C, Shen H, Wang YP, Xiao HM, Deng HW. Accurate diagnosis of colorectal cancer based on histopathology images using artificial intelligence. BMC Med 2021; 19:76. [PMID: 33752648 PMCID: PMC7986569 DOI: 10.1186/s12916-021-01942-5] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 02/16/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients' treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. METHODS Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. RESULTS Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. CONCLUSIONS This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.
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Affiliation(s)
- K S Wang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - G Yu
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - C Xu
- Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - X H Meng
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China
| | - J Zhou
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - C Zheng
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - Z Deng
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - L Shang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - R Liu
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - S Su
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - X Zhou
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - Q Li
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - J Li
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - J Wang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China
| | - K Ma
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - J Qi
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - Z Hu
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - P Tang
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - J Deng
- Department of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA
| | - X Qiu
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - B Y Li
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - W D Shen
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - R P Quan
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - J T Yang
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - L Y Huang
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - Y Xiao
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China
| | - Z C Yang
- Department of Pharmacology, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410078, Hunan, China
| | - Z Li
- School of Life Sciences, Central South University, Changsha, 410013, Hunan, China
| | - S C Wang
- College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, Hunan, China
| | - H Ren
- Department of Pathology, Gongli Hospital, Second Military Medical University, Shanghai, 200135, China
- Department of Pathology, the Peace Hospital Affiliated to Changzhi Medical College, Changzhi, 046000, China
| | - C Liang
- Pathological Laboratory of Adicon Medical Laboratory Co., Ltd, Hangzhou, 310023, Zhejiang, China
| | - W Guo
- Department of Pathology, First Affiliated Hospital of Hunan Normal University, The People's Hospital of Hunan Province, Changsha, 410005, Hunan, China
| | - Y Li
- Department of Pathology, First Affiliated Hospital of Hunan Normal University, The People's Hospital of Hunan Province, Changsha, 410005, Hunan, China
| | - H Xiao
- Department of Pathology, the Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Y Gu
- Department of Pathology, the Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - J P Yun
- Department of Pathology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - D Huang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
| | - Z Song
- Department of Pathology, Chinese PLA General Hospital, Beijing, 100853, China
| | - X Fan
- Department of Pathology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China
| | - L Chen
- Department of Pathology, The first affiliated hospital, Air Force Medical University, Xi'an, 710032, China
| | - X Yan
- Institute of Pathology and southwest cancer center, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
| | - Z Li
- Department of Pathology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Z C Huang
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - J Huang
- Department of Anatomy and Neurobiology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China
| | - J Luttrell
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
| | - C Y Zhang
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
| | - W Zhou
- College of Computing, Michigan Technological University, Houghton, MI, 49931, USA
| | - K Zhang
- Department of Computer Science, Bioinformatics Facility of Xavier NIH RCMI Cancer Research Center, Xavier University of Louisiana, New Orleans, LA, 70125, USA
| | - C Yi
- Department of Pathology, Ochsner Medical Center, New Orleans, LA, 70121, USA
| | - C Wu
- Department of Statistics, Florida State University, Tallahassee, FL, 32306, USA
| | - H Shen
- Department of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA
- Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - Y P Wang
- Department of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, 70118, USA
| | - H M Xiao
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
| | - H W Deng
- Department of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA.
- Centers of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
- Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, 70112, USA.
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