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PurposeIn this study, the aim was to comprehensively analyze the current status, hotspots, and trends of trans-oral endoscopic thyroidectomy (TOET) through bibliometric analysis and by presenting the field atlas.MethodsWeb of Science Core Collection database was adopted to screen studies regarding TOET published between January 1, 2008 and August 1, 2022. The evaluation covered the criteria total number of studies, keywords, and contributions from countries/regions, institutions, journals, and authors.ResultsA total of 229 studies were covered. SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES is the largest publication in the field of TOET. The three countries that contributed the most studies were Korea, China, and the USA. The most frequently occurring core keywords in the field of TOET are vestibular approach, outcomes, experience, safety, robotic thyroidectomy, scar, video-assisted thyroidectomy and quality-of-life. The seven clusters were generated in this study: intraoperative monitoring of the laryngeal return nerve (# 0), learning curve (# 1), postoperative quality of life (# 2), central lymph node dissection and safety (# 3), complications (# 4), minimally invasive surgery (# 5), and robotic surgery (# 6).ConclusionThe main research topics in the field of TOET place focuses on learning curves, laryngeal nerve monitoring, carbon dioxide gas bolus, chin nerve injury, surgical complications, and surgical safety. In the future, more academics will focus on the safety of the procedure and reducing complications..

Breast conserving surgery (BCS) for breast cancer is widely performed. This study aimed to identify the characteristics of the 100 most cited articles in BCS research. The 100 most cited articles were retrieved from the Web of Science datasbase. Using bibliometric tools, the contributions of countries, institutions, authors, and of research development were analyzed. The country with the highest number of manuscripts in the top 100 was the United States (n = 59). The Memorial Sloan Kettering Cancer Center and University of Pennsylvania each published 21 articles. Bartelink H, Harris JR, and Morrow M each published eight articles. Among the top 100 most cited articles, hotspots focused on breast-conserving margins, recurrence, distant metastases, radiotherapy, and some controlled trials. Surgical margin, recurrence, distant metastases, radiation therapy are the hot topics in these 100 articles. There may be new radiotherapy modalities to improve the efficacy of post-operative radiotherapy in the future. The results of this review provide breast surgeons with research highlights and hot spots in the field of BCS and predict the future. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) is more and more widely used in cancer, which is of great help to doctors in diagnosis and treatment. This study aims to summarize the current research hotspots in the Application of Artificial Intelligence in Cancer (AAIC) and to assess the research trends in AAIC. Methods: Scientific publications for AAIC-related research from 1 January 1998 to 1 July 2022 were obtained from the Web of Science database. The metrics analyses using bibliometrics software included publication, keyword, author, journal, institution, and country. In addition, the blustering analysis on the binary matrix was performed on hot keywords. Results: The total number of papers in this study is 1592. The last decade of AAIC research has been divided into a slow development phase (2013-2018) and a rapid development phase (2019-2022). An international collaboration centered in the USA is dedicated to the development and application of AAIC. Li J is the most prolific writer in AAIC. Through clustering analysis and highfrequency keyword research, it has been shown that AI plays a significantly important role in the prediction, diagnosis, treatment and prognosis of cancer. Classification, diagnosis, carcinogenesis, risk, and validation are developing topics. Eight hotspot fields of AAIC were also identified. Conclusion: AAIC can benefit cancer patients in diagnosing cancer, assessing the effectiveness of treatment, making a decision, predicting prognosis and saving costs. Future AAIC research may be dedicated to optimizing AI calculation tools, improving accuracy, and promoting AI. [ABSTRACT FROM AUTHOR]