Seminars in Vascular Surgery最新文献_第7页

Computer Science meets Vascular Surgery: Keeping a pulse on artificial intelligence 计算机科学与血管外科:保持人工智能的脉搏

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-09-01 DOI: 10.1053/j.semvascsurg.2023.05.003

Carly Thaxton , Alan Dardik

引用次数: 0

The regulatory environment for artificial intelligence–enabled devices in the United States 美国人工智能设备的监管环境

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-09-01 DOI: 10.1053/j.semvascsurg.2023.05.005

Nathan L. Liang , Timothy K. Chung , David A. Vorp

引用次数: 0

Protecting patient safety and privacy in the era of artificial intelligence 在人工智能时代保护患者安全和隐私

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-09-01 DOI: 10.1053/j.semvascsurg.2023.06.002

Andrea Alonso, Jeffrey J. Siracuse

引用次数: 0

Potential applications of artificial intelligence and machine learning on diagnosis, treatment, and outcome prediction to address health care disparities of chronic limb-threatening ischemia 人工智能和机器学习在诊断、治疗和结果预测方面的潜在应用，以解决慢性肢体威胁性缺血的医疗保健差异。

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-09-01 DOI: 10.1053/j.semvascsurg.2023.06.003

Amir Behzad Bagheri , Mohammad Dehghan Rouzi , Navid Alemi Koohbanani , Mohammad H. Mahoor , M.G. Finco , Myeounggon Lee , Bijan Najafi , Jayer Chung

{"title":"Potential applications of artificial intelligence and machine learning on diagnosis, treatment, and outcome prediction to address health care disparities of chronic limb-threatening ischemia","authors":"Amir Behzad Bagheri , Mohammad Dehghan Rouzi , Navid Alemi Koohbanani , Mohammad H. Mahoor , M.G. Finco , Myeounggon Lee , Bijan Najafi , Jayer Chung","doi":"10.1053/j.semvascsurg.2023.06.003","DOIUrl":"10.1053/j.semvascsurg.2023.06.003","url":null,"abstract":"<div>Chronic limb-threatening ischemia (CLTI) is the most advanced form of peripheral artery disease. CLTI has an extremely poor prognosis and is associated with considerable risk of major amputation, cardiac morbidity, mortality, and poor quality of life. Early diagnosis and targeted treatment of CLTI is critical for improving patient's prognosis. However, this objective has proven elusive, time-consuming, and challenging due to existing health care disparities among patients. In this article, we reviewed how artificial intelligence (AI) and machine learning (ML) can be helpful to accurately diagnose, improve outcome prediction, and identify disparities in the treatment of CLTI. We demonstrate the importance of AI/ML approaches for management of these patients and how available data could be used for computer-guided interventions. Although AI/ML applications to mitigate health care disparities in CLTI are in their infancy, we also highlighted specific AI/ML methods that show potential for addressing health care disparities in CLTI.</div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49684798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Mature artificial intelligence– and machine learning–enabled medical tools impacting vascular surgical care: A scoping review of late-stage, US Food and Drug Administration–approved or cleared technologies relevant to vascular surgeons 影响血管外科护理的成熟人工智能和机器学习医疗工具：美国食品和药物管理局批准或批准的血管外科医生相关技术的后期范围审查。

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-09-01 DOI: 10.1053/j.semvascsurg.2023.06.001

David P. Stonko, Caitlin W. Hicks

{"title":"Mature artificial intelligence– and machine learning–enabled medical tools impacting vascular surgical care: A scoping review of late-stage, US Food and Drug Administration–approved or cleared technologies relevant to vascular surgeons","authors":"David P. Stonko, Caitlin W. Hicks","doi":"10.1053/j.semvascsurg.2023.06.001","DOIUrl":"10.1053/j.semvascsurg.2023.06.001","url":null,"abstract":"<div>Artificial intelligence and machine learning (AI/ML)-enabled tools are shifting from theoretical or research-only applications to mature, clinically useful tools. The goal of this article was to provide a scoping review of the most mature AI/ML-enabled technologies reviewed and cleared by the US Food and Drug Administration relevant to the field of vascular surgery. Despite decades of slow progress, this landscape is now evolving rapidly, with more than 100 AI/ML-powered tools being approved by the US Food and Drug Administration each year. Within the field of vascular surgery specifically, this review identified 17 companies with mature technologies that have at least one US Food and Drug Administration clearance, all occurring between 2016 and 2022. The maturation of these technologies appears to be accelerating, with improving regulatory clarity and clinical uptake. The early AI/ML-powered devices extend or amplify clinically entrenched platform technologies and tend to be focused on the diagnosis or evaluation of time-sensitive, clinically important pathologies (eg, reading Digital Imaging and Communications in Medicine–compliant computed tomography images to identify pulmonary embolism), or when physician efficiency or time savings is improved (eg, preoperative planning and intraoperative guidance). The majority (>75%) of these technologies are at the intersection of radiology and vascular surgery. It is becoming increasingly important that the contemporary vascular surgeon understands this shifting paradigm, as these once-nascent technologies are finally maturing and will be encountered with increasingly regularity in daily clinical practice.</div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589449/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49684761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence–based predictive models in vascular diseases 基于人工智能的血管疾病预测模型

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-09-01 DOI: 10.1053/j.semvascsurg.2023.05.002

Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort

{"title":"Artificial intelligence–based predictive models in vascular diseases","authors":"Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort","doi":"10.1053/j.semvascsurg.2023.05.002","DOIUrl":"10.1053/j.semvascsurg.2023.05.002","url":null,"abstract":"<div>Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personalized medicine would benefit from novel tools to better predict individual prognosis and outcomes after intervention. Artificial intelligence (AI) has brought new insights to cardiovascular medicine, especially with the use of machine learning techniques that allow the identification of hidden patterns and complex associations in health data without any a priori assumptions. This review provides an overview on the use of artificial intelligence–based prediction models in vascular diseases, specifically focusing on aortic aneurysm, lower extremity arterial disease, and carotid stenosis. Potential benefits include the development of precision medicine in patients with vascular diseases. In addition, the main challenges that remain to be overcome to integrate artificial intelligence–based predictive models in clinical practice are discussed.</div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43168363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sex differences in outcomes of exercise therapy for patients with intermittent claudication: A scoping review 间歇性跛行患者运动治疗结果的性别差异:一项范围综述

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-08-25 DOI: 10.1053/j.semvascsurg.2023.08.001

M. Libby Weaver , Laura T. Boitano , Brian J. Fazzone , Jonathan R. Krebs , Andrea H. Denton , Pranav Kapoor , Corey A. Kalbaugh , Jessica P. Simons

{"title":"Sex differences in outcomes of exercise therapy for patients with intermittent claudication: A scoping review","authors":"M. Libby Weaver , Laura T. Boitano , Brian J. Fazzone , Jonathan R. Krebs , Andrea H. Denton , Pranav Kapoor , Corey A. Kalbaugh , Jessica P. Simons","doi":"10.1053/j.semvascsurg.2023.08.001","DOIUrl":"10.1053/j.semvascsurg.2023.08.001","url":null,"abstract":"<div>Exercise therapy is first-line treatment for intermittent claudication due to peripheral artery disease. We sought to synthesize the literature on sex differences in response to exercise therapy for the treatment of intermittent claudication due to peripheral artery disease. A scoping review was performed (1997 to 2023) using Ovid MEDLINE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Embase, SPORTDiscus, and Web of Science. Articles were included if they were a scientific report of any measures of health-related quality of life or walking performance after an intervention that included a structured walking program. Of the 13 studies, 11 included measures of walking distance; 7 included measures of walking time, 5 included measures of walking speed, and 4 included quality of life measures. Overall, exercise therapy resulted in significant improvements across most measures of walking performance for both men and females. When comparing magnitudes of outcome improvement by sex, results of walking-based measures were contradictory; some studies noted no difference and others found superior outcomes for men. Results of quality of life–based measures were also contradictory, with some finding no difference and others reporting substantially more improvement for females. Both men and females experienced considerable improvement in walking performance and quality of life with exercise therapy. Evidence regarding the differential effect of exercise therapy on outcomes by sex for intermittent claudication is limited and contradictory. Further efforts should be directed at using standardized interventions and metrics for measuring the outcomes that match the indications for intervention in these patients to better understand the expected benefits and any variance according to sex.</div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45944735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Considerations in the Application of Artificial Intelligence in Vascular Surgical Education 人工智能在血管外科教学中应用的思考

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-08-01 DOI: 10.1053/j.semvascsurg.2023.07.004

D. Rigberg, J. Jim

引用次数: 0

Mature AI/ML-Enabled Medical Tools Impacting Vascular Surgical Care: A scoping review of late-stage, FDA approved/cleared technologies relevant to vascular surgeons 影响血管外科护理的成熟人工智能/机器学习医疗工具:对后期、FDA批准/清除的血管外科相关技术的范围审查

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-06-01 DOI: 10.1053/j.semvascsurg.2023.06.001

David P. Stonko, C. Hicks

{"title":"Mature AI/ML-Enabled Medical Tools Impacting Vascular Surgical Care: A scoping review of late-stage, FDA approved/cleared technologies relevant to vascular surgeons","authors":"David P. Stonko, C. Hicks","doi":"10.1053/j.semvascsurg.2023.06.001","DOIUrl":"https://doi.org/10.1053/j.semvascsurg.2023.06.001","url":null,"abstract":"Artificial intelligence and machine learning (AI/ML)-enabled tools are shifting from theoretical or research-only applications to mature, clinically useful tools. The goal of this article was to provide a scoping review of the most mature AI/ML-enabled technologies reviewed and cleared by the US Food and Drug Administration relevant to the field of vascular surgery. Despite decades of slow progress, this landscape is now evolving rapidly, with more than 100 AI/ML-powered tools being approved by the US Food and Drug Administration each year. Within the field of vascular surgery specifically, this review identified 17 companies with mature technologies that have at least one US Food and Drug Administration clearance, all occurring between 2016 and 2022. The maturation of these technologies appears to be accelerating, with improving regulatory clarity and clinical uptake. The early AI/ML-powered devices extend or amplify clinically entrenched platform technologies and tend to be focused on the diagnosis or evaluation of time-sensitive, clinically important pathologies (eg, reading Digital Imaging and Communications in Medicine-compliant computed tomography images to identify pulmonary embolism), or when physician efficiency or time savings is improved (eg, preoperative planning and intraoperative guidance). The majority (>75%) of these technologies are at the intersection of radiology and vascular surgery. It is becoming increasingly important that the contemporary vascular surgeon understands this shifting paradigm, as these once-nascent technologies are finally maturing and will be encountered with increasingly regularity in daily clinical practice.","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46777706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Potential applications of artificial intelligence (AI) and machine learning (ML) on diagnosis, treatment, outcome prediction to address health care disparities of chronic limb-threatening ischemia (CLTI) 人工智能(AI)和机器学习(ML)在慢性肢体威胁缺血(CLTI)诊断、治疗和预后预测方面的潜在应用

IF 2.5 3区医学

Seminars in Vascular Surgery Pub Date : 2023-06-01 DOI: 10.1053/j.semvascsurg.2023.06.003

Amirbehzad Bagheri, Mohammad Dehghan Rouzi, Navid Alemi Koohbanani, M. Mahoor, MG Finco, Myeounggon Lee, B. Najafi, Jayer Chung

{"title":"Potential applications of artificial intelligence (AI) and machine learning (ML) on diagnosis, treatment, outcome prediction to address health care disparities of chronic limb-threatening ischemia (CLTI)","authors":"Amirbehzad Bagheri, Mohammad Dehghan Rouzi, Navid Alemi Koohbanani, M. Mahoor, MG Finco, Myeounggon Lee, B. Najafi, Jayer Chung","doi":"10.1053/j.semvascsurg.2023.06.003","DOIUrl":"https://doi.org/10.1053/j.semvascsurg.2023.06.003","url":null,"abstract":"Chronic limb-threatening ischemia (CLTI) is the most advanced form of peripheral artery disease. CLTI has an extremely poor prognosis and is associated with considerable risk of major amputation, cardiac morbidity, mortality, and poor quality of life. Early diagnosis and targeted treatment of CLTI is critical for improving patient's prognosis. However, this objective has proven elusive, time-consuming, and challenging due to existing health care disparities among patients. In this article, we reviewed how artificial intelligence (AI) and machine learning (ML) can be helpful to accurately diagnose, improve outcome prediction, and identify disparities in the treatment of CLTI. We demonstrate the importance of AI/ML approaches for management of these patients and how available data could be used for computer-guided interventions. Although AI/ML applications to mitigate health care disparities in CLTI are in their infancy, we also highlighted specific AI/ML methods that show potential for addressing health care disparities in CLTI.","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45834884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5