发布求助
文献互助 智能选刊 最新文献

WArtificial Intelligence in Cancer最新文献

筛选
英文 中文
Past, present, and future perspectives of ultrasound-guided ablation of liver tumors: Where could artificial intelligence lead interventional oncology? 超声引导下肝脏肿瘤消融的过去、现在和未来展望：人工智能可将介入肿瘤学引向何方？
WArtificial Intelligence in Cancer Pub Date : 2024-07-18 DOI: 10.35713/aic.v5.i1.96690
P. Tombesi, Andrea Cutini, Valentina Grasso, Francesca Di Vece, Ugo Politti, Eleonora Capatti, Florence Labb, Stefano Petaccia, Sergio Sartori
{"title":"Past, present, and future perspectives of ultrasound-guided ablation of liver tumors: Where could artificial intelligence lead interventional oncology?","authors":"P. Tombesi, Andrea Cutini, Valentina Grasso, Francesca Di Vece, Ugo Politti, Eleonora Capatti, Florence Labb, Stefano Petaccia, Sergio Sartori","doi":"10.35713/aic.v5.i1.96690","DOIUrl":"https://doi.org/10.35713/aic.v5.i1.96690","url":null,"abstract":"The first ablation procedures for small hepatocellular carcinomas were percutaneous ethanol injection under ultrasound (US) guidance. Later, radiofrequency ablation was shown to achieve larger coagulation areas than percutaneous ethanol injection and became the most used ablation technique worldwide. In the past decade, microwave ablation systems have achieved larger ablation areas than radiofrequency ablation, suggesting that the 3-cm barrier could be broken in the treatment of liver tumors. Likewise, US techniques to guide percutaneous ablation have seen important progress. Contrast-enhanced US (CEUS) can define and target the tumor better than US and can assess the size of the ablation area after the procedure, which allows immediate retreatment of the residual tumor foci. Furthermore, fusion imaging fuses real-time US images with computed tomography or magnetic resonance imaging with significant improvements in detecting and targeting lesions with low conspicuity on CEUS. Recently, software powered by artificial intelligence has been developed to allow three-dimensional segmentation and reconstruction of the anatomical structures, aiding in procedure planning, assessing ablation completeness, and targeting the residual viable foci with greater precision than CEUS. Hopefully, this could lead to the ablation of tumors up to 5-7 cm in size.","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":" 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions 人工智能在甲状腺癌诊断中的应用:最新进展和未来发展方向
WArtificial Intelligence in Cancer Pub Date : 2023-09-08 DOI: 10.35713/aic.v4.i1.1
Lakshmi Nagendra, Joseph M Pappachan, C. Fernandez
{"title":"Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions","authors":"Lakshmi Nagendra, Joseph M Pappachan, C. Fernandez","doi":"10.35713/aic.v4.i1.1","DOIUrl":"https://doi.org/10.35713/aic.v4.i1.1","url":null,"abstract":"The diagnosis and management of thyroid cancer is fraught with challenges despite the advent of innovative diagnostic, surgical, and chemotherapeutic modalities. Challenges like inaccuracy in prognostication, uncertainty in cytopathological diagnosis, trouble in differentiating follicular neoplasms, intra-observer and inter-observer variability on ultrasound imaging preclude personalised treatment in thyroid cancer. Artificial intelligence (AI) is bringing a paradigm shift to the healthcare, powered by quick advancement of the analytic techniques. Several recent studies have shown remarkable progress in thyroid cancer diagnostics based on AI-assisted algorithms. Application of AI techniques in thyroid ultrasonography and cytopathology have shown remarkable impro-vement in sensitivity and specificity over the traditional diagnostic modalities. AI has also been explored in the development of treatment algorithms for indeterminate nodules and for prognostication in the patients with thyroid cancer. The benefits of high repeatability and straightforward implementation of AI in the management of thyroid cancer suggest that it holds promise for clinical application. Limited clinical experience and lack of prospective validation studies remain the biggest drawbacks. Developing verified and trustworthy algorithms after extensive testing and validation using prospective, multi-centre trials is crucial for the future use of AI in the pipeline of precision medicine in the management of thyroid cancer.","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123858101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Building and evaluating an artificial intelligence algorithm: A practical guide for practicing oncologists 构建和评估人工智能算法:执业肿瘤学家的实用指南
WArtificial Intelligence in Cancer Pub Date : 2022-07-28 DOI: 10.35713/aic.v3.i3.42
Anupama Ramachandran, Deeksha Bhalla, K. Rangarajan, R. Pramanik, Subhashis Banerjee, Chetan Arora
{"title":"Building and evaluating an artificial intelligence algorithm: A practical guide for practicing oncologists","authors":"Anupama Ramachandran, Deeksha Bhalla, K. Rangarajan, R. Pramanik, Subhashis Banerjee, Chetan Arora","doi":"10.35713/aic.v3.i3.42","DOIUrl":"https://doi.org/10.35713/aic.v3.i3.42","url":null,"abstract":"","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133739792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Potential and role of artificial intelligence in current medical healthcare 人工智能在当前医疗保健中的潜力和作用
WArtificial Intelligence in Cancer Pub Date : 2022-02-28 DOI: 10.35713/aic.v3.i1.1
Chao-Ming Hung, Hongfeng Shi, Po-Huang Lee, Chao-Sung Chang, K. Rau, Hui-Ming Lee, Cheng-Hao Tseng, S. Pei, K. Tsai, C. Chiu
{"title":"Potential and role of artificial intelligence in current medical healthcare","authors":"Chao-Ming Hung, Hongfeng Shi, Po-Huang Lee, Chao-Sung Chang, K. Rau, Hui-Ming Lee, Cheng-Hao Tseng, S. Pei, K. Tsai, C. Chiu","doi":"10.35713/aic.v3.i1.1","DOIUrl":"https://doi.org/10.35713/aic.v3.i1.1","url":null,"abstract":"","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121194294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Artificial intelligence as a future in cancer surgery 人工智能在癌症手术中的应用前景
WArtificial Intelligence in Cancer Pub Date : 2022-02-28 DOI: 10.35713/aic.v3.i1.11
M. Burati, F. Tagliabue, Adriana Lomonaco, M. Chiarelli, M. Zago, Gerardo Cioffi, U. Cioffi
{"title":"Artificial intelligence as a future in cancer surgery","authors":"M. Burati, F. Tagliabue, Adriana Lomonaco, M. Chiarelli, M. Zago, Gerardo Cioffi, U. Cioffi","doi":"10.35713/aic.v3.i1.11","DOIUrl":"https://doi.org/10.35713/aic.v3.i1.11","url":null,"abstract":"","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133252170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence in colorectal cancer management 人工智能在结直肠癌管理中的应用
WArtificial Intelligence in Cancer Pub Date : 2021-12-29 DOI: 10.35713/aic.v2.i6.79
P. Cianci, E. Restini
{"title":"Artificial intelligence in colorectal cancer management","authors":"P. Cianci, E. Restini","doi":"10.35713/aic.v2.i6.79","DOIUrl":"https://doi.org/10.35713/aic.v2.i6.79","url":null,"abstract":"Artificial intelligence (AI) is a new branch of computer science involving many disciplines and technologies. Since its application in the medical field, it has been constantly studied and developed. AI includes machine learning and neural networks to create new technologies or to improve existing ones. Various AI supporting systems are available for a personalized and novel strategy for the management of colorectal cancer (CRC). This mini-review aims to summarize the progress of research and possible clinical applications of AI in the investigation, early diagnosis, treatment, and management of CRC, to offer elements of knowledge as a starting point for new studies and future applications. applications the field of This mini-review to open a window on the attempts being made on the application of artificial intelligence in the scientific and clinical research of colorectal cancer by summarizing the most evident results. Our aim is not to draw definitive conclusions but to stimulate the interest of researchers in the application of these new technologies, which seem to be able to offer valuable help in the near future.","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134360974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Artificial intelligence reveals roles of gut microbiota in driving human colorectal cancer evolution 人工智能揭示肠道微生物群在驱动人类结直肠癌进化中的作用
WArtificial Intelligence in Cancer Pub Date : 2021-10-28 DOI: 10.35713/aic.v2.i5.69
Xueting Wan
{"title":"Artificial intelligence reveals roles of gut microbiota in driving human colorectal cancer evolution","authors":"Xueting Wan","doi":"10.35713/aic.v2.i5.69","DOIUrl":"https://doi.org/10.35713/aic.v2.i5.69","url":null,"abstract":"","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122550295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial neural network for prediction of acute kidney injury after liver transplantation for cirrhosis and hepatocellular carcinoma 人工神经网络预测肝硬化、肝癌肝移植术后急性肾损伤
WArtificial Intelligence in Cancer Pub Date : 2021-10-28 DOI: 10.35713/aic.v2.i5.51
L. Bredt, L. Peres
{"title":"Artificial neural network for prediction of acute kidney injury after liver transplantation for cirrhosis and hepatocellular carcinoma","authors":"L. Bredt, L. Peres","doi":"10.35713/aic.v2.i5.51","DOIUrl":"https://doi.org/10.35713/aic.v2.i5.51","url":null,"abstract":"Acute kidney injury (AKI) has serious consequences on the prognosis of patients undergoing liver transplantation (LT) for liver cancer and cirrhosis. Artificial neural network (ANN) has recently been proposed as a useful tool in many fields in the setting of solid organ transplantation and surgical oncology, where patient prognosis depends on a multidimensional and nonlinear relationship between variables pertaining to the surgical procedure, the donor (graft characteristics), and the recipient comorbidities. In the specific case of LT, ANN models have been developed mainly to predict survival in patients with cirrhosis, to assess the best donor-to-recipient match during allocation processes, and to foresee postoperative complications and outcomes. This is a specific opinion review on the role of ANN in the prediction of AKI after LT for liver cancer and cirrhosis, highlighting potential strengths of the method to forecast this serious postoperative complication.","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125047116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Repairing the human with artificial intelligence in oncology 用肿瘤领域的人工智能修复人类
WArtificial Intelligence in Cancer Pub Date : 2021-10-28 DOI: 10.35713/aic.v2.i5.60
Ian Morilla
{"title":"Repairing the human with artificial intelligence in oncology","authors":"Ian Morilla","doi":"10.35713/aic.v2.i5.60","DOIUrl":"https://doi.org/10.35713/aic.v2.i5.60","url":null,"abstract":"Artificial intelligence is a groundbreaking tool to learn and analyse higher features extracted from any dataset at large scale. This ability makes it ideal to facing any complex problem that may generally arise in the biomedical domain or oncology in particular. In this work, we envisage to provide a global vision of this mathematical discipline outgrowth by linking some other related subdomains such as transfer, reinforcement or federated learning. Complementary, we also introduce the recently popular method of topological data analysis that improves the performance of learning models.","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116915168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
How is artificial intelligence applied in solid tumor imaging? 人工智能在实体肿瘤成像中的应用?
WArtificial Intelligence in Cancer Pub Date : 2021-08-28 DOI: 10.35713/aic.v2.i4.49
Jianshe Yang, Qiang Wang
{"title":"How is artificial intelligence applied in solid tumor imaging?","authors":"Jianshe Yang, Qiang Wang","doi":"10.35713/aic.v2.i4.49","DOIUrl":"https://doi.org/10.35713/aic.v2.i4.49","url":null,"abstract":"","PeriodicalId":415276,"journal":{"name":"WArtificial Intelligence in Cancer","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126946072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信