In the era of big data,where vast amounts of information are being generated and collected at an unprecedented rate,there is a pressing demand for innovative data-driven multi-modal fusion methods.These methods aim to...In the era of big data,where vast amounts of information are being generated and collected at an unprecedented rate,there is a pressing demand for innovative data-driven multi-modal fusion methods.These methods aim to integrate diverse neuroimaging per-spectives to extract meaningful insights and attain a more comprehensive understanding of complex psychiatric disorders.However,analyzing each modality separately may only reveal partial insights or miss out on important correlations between different types of data.This is where data-driven multi-modal fusion techniques come into play.By combining information from multiple modalities in a synergistic manner,these methods enable us to uncover hidden patterns and relationships that would otherwise remain unnoticed.In this paper,we present an extensive overview of data-driven multimodal fusion approaches with or without prior information,with specific emphasis on canonical correlation analysis and independent component analysis.The applications of such fusion methods are wide-ranging and allow us to incorporate multiple factors such as genetics,environment,cognition,and treatment outcomes across various brain disorders.After summarizing the diverse neuropsychiatric magnetic resonance imaging fusion applications,we further discuss the emerging neuroimaging analyzing trends in big data,such as N-way multimodal fusion,deep learning approaches,and clinical translation.Overall,multimodal fusion emerges as an imperative approach providing valuable insights into the under-lying neural basis of mental disorders,which can uncover subtle abnormalities or potential biomarkers that may benefit targeted treatments and personalized medical interventions.展开更多
Introduction: Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma, but it represents only a small portion of soft tissue sarcoma in adult population. There is a treatment protocol based on Intergro...Introduction: Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma, but it represents only a small portion of soft tissue sarcoma in adult population. There is a treatment protocol based on Intergroup Rhabdomyosarcoma Study (IRS) that provides satisfactory results in treating RMS in children, but there is only limited evidence regarding the outcome and prognosis in extrapolating the IRS protocol to treat RMS in adults. We report a case of adult pleomorphic RMS treated with multidisciplinary approach and the results we have obtained. Case presentation: A 48-year-old woman was admitted in February 2011 due to a painful mass on her left thigh. Diagnosis of pleomorphic rhabdomyosarcoma was made by histopathology and immunohistochemistry. After multimodal treatment that includes Trans-Arterial Chemotherapy Infusion, Cryosurgery, and wide excision surgery, our patient remains disease-free as of the latest annual follow up examination on June 2017. Conclusions: The pleomorphic type of Rhabdomyosarcoma is very rare in adults and is often associated with a poor prognosis. In our case, a multidisciplinary approach with multimodal treatment provides excellent result, even after a routine follow up spanning through six years.展开更多
产后疼痛是困扰产妇的常见问题,如治疗不当可能会导致阿片类药物滥用、产后抑郁和疼痛长期存在等不良后果。因此,美国妇产科医师学会(American College of Obstetricians and Gynecologists,ACOG)于2021年9月提出了针对产后疼痛的临床共...产后疼痛是困扰产妇的常见问题,如治疗不当可能会导致阿片类药物滥用、产后抑郁和疼痛长期存在等不良后果。因此,美国妇产科医师学会(American College of Obstetricians and Gynecologists,ACOG)于2021年9月提出了针对产后疼痛的临床共识,专门对产后疼痛的一般管理、阴道分娩、剖宫产术后、母乳喂养时及出院后疼痛的处置给出了治疗建议与指导,强调了阶梯式多模式药物镇痛方法与个体化用药原则。推荐临床用药可遵循“非阿片类镇痛药(如对乙酰氨基酚和非甾体抗炎药)—弱阿片类药物—强阿片类药物(必要时)”阶梯式给药原则,并可合理联合用药。对此进行简要介绍与要点解读。展开更多
本文以Kress & Van Leeuwen视觉图像的分析框架和系统功能语言学理论为依托,对一则环保公益广告的再现、互动和构图意义进行了详尽的分析,指出以多模态非线性方式出现的广告语篇中多种符号模态(如语言、色彩、图像、印刷体式等)之...本文以Kress & Van Leeuwen视觉图像的分析框架和系统功能语言学理论为依托,对一则环保公益广告的再现、互动和构图意义进行了详尽的分析,指出以多模态非线性方式出现的广告语篇中多种符号模态(如语言、色彩、图像、印刷体式等)之间相互作用、共建意义,证明了传统语篇分析模式的局限性,同时也体现出系统功能语法在对包含图像的广告语篇分析中具有较强的优越性。展开更多
基金supported by the Natural Science Foundation of China (62373062,82022035)the China Postdoctoral Science Foundation (2022M710434)+1 种基金the National Institute of Health grants (R01EB005846,R01MH117107,and R01MH118695)the National Science Foundation (2112455).
文摘In the era of big data,where vast amounts of information are being generated and collected at an unprecedented rate,there is a pressing demand for innovative data-driven multi-modal fusion methods.These methods aim to integrate diverse neuroimaging per-spectives to extract meaningful insights and attain a more comprehensive understanding of complex psychiatric disorders.However,analyzing each modality separately may only reveal partial insights or miss out on important correlations between different types of data.This is where data-driven multi-modal fusion techniques come into play.By combining information from multiple modalities in a synergistic manner,these methods enable us to uncover hidden patterns and relationships that would otherwise remain unnoticed.In this paper,we present an extensive overview of data-driven multimodal fusion approaches with or without prior information,with specific emphasis on canonical correlation analysis and independent component analysis.The applications of such fusion methods are wide-ranging and allow us to incorporate multiple factors such as genetics,environment,cognition,and treatment outcomes across various brain disorders.After summarizing the diverse neuropsychiatric magnetic resonance imaging fusion applications,we further discuss the emerging neuroimaging analyzing trends in big data,such as N-way multimodal fusion,deep learning approaches,and clinical translation.Overall,multimodal fusion emerges as an imperative approach providing valuable insights into the under-lying neural basis of mental disorders,which can uncover subtle abnormalities or potential biomarkers that may benefit targeted treatments and personalized medical interventions.
文摘Introduction: Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma, but it represents only a small portion of soft tissue sarcoma in adult population. There is a treatment protocol based on Intergroup Rhabdomyosarcoma Study (IRS) that provides satisfactory results in treating RMS in children, but there is only limited evidence regarding the outcome and prognosis in extrapolating the IRS protocol to treat RMS in adults. We report a case of adult pleomorphic RMS treated with multidisciplinary approach and the results we have obtained. Case presentation: A 48-year-old woman was admitted in February 2011 due to a painful mass on her left thigh. Diagnosis of pleomorphic rhabdomyosarcoma was made by histopathology and immunohistochemistry. After multimodal treatment that includes Trans-Arterial Chemotherapy Infusion, Cryosurgery, and wide excision surgery, our patient remains disease-free as of the latest annual follow up examination on June 2017. Conclusions: The pleomorphic type of Rhabdomyosarcoma is very rare in adults and is often associated with a poor prognosis. In our case, a multidisciplinary approach with multimodal treatment provides excellent result, even after a routine follow up spanning through six years.
文摘产后疼痛是困扰产妇的常见问题,如治疗不当可能会导致阿片类药物滥用、产后抑郁和疼痛长期存在等不良后果。因此,美国妇产科医师学会(American College of Obstetricians and Gynecologists,ACOG)于2021年9月提出了针对产后疼痛的临床共识,专门对产后疼痛的一般管理、阴道分娩、剖宫产术后、母乳喂养时及出院后疼痛的处置给出了治疗建议与指导,强调了阶梯式多模式药物镇痛方法与个体化用药原则。推荐临床用药可遵循“非阿片类镇痛药(如对乙酰氨基酚和非甾体抗炎药)—弱阿片类药物—强阿片类药物(必要时)”阶梯式给药原则,并可合理联合用药。对此进行简要介绍与要点解读。
文摘本文以Kress & Van Leeuwen视觉图像的分析框架和系统功能语言学理论为依托,对一则环保公益广告的再现、互动和构图意义进行了详尽的分析,指出以多模态非线性方式出现的广告语篇中多种符号模态(如语言、色彩、图像、印刷体式等)之间相互作用、共建意义,证明了传统语篇分析模式的局限性,同时也体现出系统功能语法在对包含图像的广告语篇分析中具有较强的优越性。
