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  1. Article ; Online: Shifting tides: reflecting on medical education in the time of covid-19.

    Cheng, Monica

    BMJ (Clinical research ed.)

    2022  Volume 376, Page(s) o657

    MeSH term(s) COVID-19 ; Education, Medical ; Humans
    Language English
    Publishing date 2022-03-11
    Publishing country England
    Document type Personal Narrative
    ZDB-ID 1362901-3
    ISSN 1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    ISSN (online) 1756-1833
    ISSN 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    DOI 10.1136/bmj.o657
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    Ua VI Zs.10: Show issues Location:
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  2. Article ; Online: Harnessing the Potential of Artificial Intelligence for Quality Assurance in Radiology Practice.

    Cheng, Monica / Lee, Christoph I

    Journal of the American College of Radiology : JACR

    2023  Volume 20, Issue 12, Page(s) 1231–1232

    MeSH term(s) Artificial Intelligence ; Radiology ; Radiography ; Radiologists
    Language English
    Publishing date 2023-07-07
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2274861-1
    ISSN 1558-349X ; 1546-1440
    ISSN (online) 1558-349X
    ISSN 1546-1440
    DOI 10.1016/j.jacr.2023.06.011
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6636: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  3. Article: Highly variable biodistribution of

    Cheng, Monica / Tann, Mark

    Hepatobiliary surgery and nutrition

    2022  Volume 11, Issue 5, Page(s) 654–661

    Abstract: Background: Somatostatin receptor (SSTR)-targeted positron emission tomography/computed tomography (PET/CT) imaging has risen to the forefront for neuroendocrine tumor (NET) detection and management, yet the variability of significant uptake variability ...

    Abstract Background: Somatostatin receptor (SSTR)-targeted positron emission tomography/computed tomography (PET/CT) imaging has risen to the forefront for neuroendocrine tumor (NET) detection and management, yet the variability of significant uptake variability (SUV) as a semiquantitative measure of disease detection and tumor response to treatment has not been fully explored.
    Methods: We assess the reproducibility and interscan variability of SUV metrics of normal tissue and NET in serial
    Results: Both primary and metastatic hepatic lesions demonstrated SUV (SUV
    Conclusions: The highly variable nature of regional SUV
    Language English
    Publishing date 2022-01-28
    Publishing country China (Republic : 1949- )
    Document type Journal Article
    ZDB-ID 2812398-0
    ISSN 2304-389X ; 2304-3881
    ISSN (online) 2304-389X
    ISSN 2304-3881
    DOI 10.21037/hbsn-21-554
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  4. Article ; Online: Trust: The Foundation of Radiologic Excellence.

    Cheng, Monica / Gunderman, Richard B

    AJR. American journal of roentgenology

    2020  Volume 215, Issue 4, Page(s) 1037–1038

    Abstract: OBJECTIVE. ...

    Abstract OBJECTIVE.
    MeSH term(s) Humans ; Interprofessional Relations ; Radiology ; Trust
    Language English
    Publishing date 2020-07-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 82076-3
    ISSN 1546-3141 ; 0361-803X ; 0092-5381
    ISSN (online) 1546-3141
    ISSN 0361-803X ; 0092-5381
    DOI 10.2214/AJR.19.22658
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    In stock of ZB MED Cologne/Königswinter

    Ue I Zs.57: Show issues Location:
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  5. Article: Is obesity a disease?-the evolving concepts, cancer paradox and association with improved cancer immunotherapy efficacy.

    Cheng, Monica / Gunderman, Richard B

    Hepatobiliary surgery and nutrition

    2019  Volume 9, Issue 2, Page(s) 247–249

    Language English
    Publishing date 2019-06-12
    Publishing country China (Republic : 1949- )
    Document type Editorial ; Comment
    ZDB-ID 2812398-0
    ISSN 2304-389X ; 2304-3881
    ISSN (online) 2304-389X
    ISSN 2304-3881
    DOI 10.21037/hbsn.2019.11.35
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  6. Article ; Online: In Vivo Quantitative Whole-Body Perfusion Imaging Using Radiolabeled Copper(II) Bis(Thiosemicarbazone) Complexes and Positron Emission Tomography (PET).

    Green, Mark A / Mathias, Carla J / Smith, Nathaniel J / Cheng, Monica / Hutchins, Gary D

    Methods in molecular biology (Clifton, N.J.)

    2021  Volume 2393, Page(s) 751–771

    Abstract: Traditional quantitative perfusion imaging methods require complex data acquisition and analysis strategies; typically require ancillary arterial blood sampling for measurement of input functions; are limited to single organ or tissue regions in an ... ...

    Abstract Traditional quantitative perfusion imaging methods require complex data acquisition and analysis strategies; typically require ancillary arterial blood sampling for measurement of input functions; are limited to single organ or tissue regions in an imaging session; and because of their complexity, are not well suited for routine clinical implementation in a standardized fashion that can be readily repeated across diverse clinical sites. The whole-body perfusion method described in this chapter has the advantages of on-demand radiotracer production; simple tissue pharmacokinetics enabling standardized estimation of perfusion; short-lived radionuclides, facilitating repeat or combination imaging procedures; and scalability to support widespread clinical implementation. This method leverages the unique physiological characteristics of radiolabeled copper(II) bis(thiosemicarbazone) complexes and the detection sensitivity of positron emission tomography (PET) to produce quantitatively accurate whole-body perfusion images. This chapter describes the synthesis of ethylglyoxal bis(thosemicarbazonato)copper(II) labeled with copper-62 ([
    MeSH term(s) Copper ; Perfusion ; Perfusion Imaging ; Positron-Emission Tomography ; Thiosemicarbazones
    Chemical Substances Thiosemicarbazones ; Copper (789U1901C5)
    Language English
    Publishing date 2021-11-27
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-1803-5_40
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  7. Article ; Online: Fat-containing adnexal masses on MRI: solid tissue volume and fat distribution as a guide for O-RADS Score assignment.

    Cheng, Monica / Causa Andrieu, Pamela / Kim, Tae-Hyung / Gangai, Natalie / Sonoda, Yukio / Hricak, Hedvig / Lakhman, Yulia / Vargas, Hebert A / Woo, Sungmin

    Abdominal radiology (New York)

    2022  Volume 48, Issue 1, Page(s) 358–366

    Abstract: Purpose: To explore ways to improve O-RADS MRI scoring for fat-containing adnexal masses, by investigating methods for quantifying solid tissue volume and fat distribution and evaluating their associations with malignancy.: Methods: This ... ...

    Abstract Purpose: To explore ways to improve O-RADS MRI scoring for fat-containing adnexal masses, by investigating methods for quantifying solid tissue volume and fat distribution and evaluating their associations with malignancy.
    Methods: This retrospective, single-center study included patients with fat-containing adnexal masses on MRI during 2008-2021. Two radiologists independently reviewed overall size (Size
    Results: 188 women (median age 35 years) with 163 benign and 25 malignant lesions were included. Size
    Conclusion: Overall size, size of (any or non-Rokitansky-nodule) solid tissue, and fat distribution differed between benign and malignant fat-containing adnexal masses. Incorporating these would constitute simple and practical approaches to refining O-RADS MRI scoring.
    MeSH term(s) Humans ; Female ; Adult ; Retrospective Studies ; Magnetic Resonance Imaging/methods ; Adnexal Diseases/diagnostic imaging ; Sensitivity and Specificity ; Radiologists
    Language English
    Publishing date 2022-09-29
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2839786-1
    ISSN 2366-0058 ; 2366-004X
    ISSN (online) 2366-0058
    ISSN 2366-004X
    DOI 10.1007/s00261-022-03688-x
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1262: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Medication Complexity Among Older Adults with HF: How Can We Assess Better?

    Kwak, Min Ji / Cheng, Monica / Goyal, Parag / Kim, Dae Hyun / Hummel, Scott L / Dhoble, Abhijeet / Deshmukh, Ashish / Aparasu, Rajender / Holmes, Holly M

    Drugs & aging

    2022  Volume 39, Issue 11, Page(s) 851–861

    Abstract: Medical management of heart failure (HF) has evolved and has achieved significant survival benefits, resulting in highly complex medication regimens. Complex medication regimens create challenges for older adults, including nonadherence and increased ... ...

    Abstract Medical management of heart failure (HF) has evolved and has achieved significant survival benefits, resulting in highly complex medication regimens. Complex medication regimens create challenges for older adults, including nonadherence and increased adverse drug events, especially associated with cognitive impairment, physical limitations, or lack of social support. However, the association between medication complexity and patients' health outcomes among older adults with HF is unclear. The purpose of this review is to address how the complexity of HF medications has been assessed in the literature and what clinical outcomes are associated with medication regimen complexity in HF. Further, we aimed to explore how older adults were represented in those studies. The Medication Regimen Complexity Index was the most commonly used tool for assessment of medication regimen complexity. Rehospitalization was most frequently assessed as the clinical outcome, and other studies used medication adherence, quality of life, healthcare utilization, healthcare cost, or side effect. However, the studies showed inconsistent results in the association between the medication regimen complexity and clinical outcomes. We also identified an extremely small number of studies that focused on older adults. Notably, current medication regimen complexity tools did not consider a complicated clinical condition of an older adult with multimorbidity, therapeutic competition, drug interactions, or altered tolerance to the usual dose strength of the medications. Furthermore, the outcomes that studies assessed were rarely comprehensive or patient centered. More studies are required to fill the knowledge gap identifying more comprehensive and accurate medication regimen complexity tools and more patient-centered outcome assessment.
    MeSH term(s) Humans ; Aged ; Quality of Life ; Medication Adherence/psychology ; Heart Failure/drug therapy ; Drug-Related Side Effects and Adverse Reactions
    Language English
    Publishing date 2022-10-13
    Publishing country New Zealand
    Document type Journal Article ; Review ; Research Support, N.I.H., Extramural
    ZDB-ID 1075770-3
    ISSN 1179-1969 ; 1170-229X
    ISSN (online) 1179-1969
    ISSN 1170-229X
    DOI 10.1007/s40266-022-00979-2
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    Zs.A 3481: Show issues Location:
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  9. Article: Predicting progression of

    Cheng, Monica / Hanna, Nasser H / Davidson, Darrell D / Gunderman, Richard B

    Journal of thoracic disease

    2019  Volume 11, Issue 6, Page(s) 2222–2225

    Language English
    Publishing date 2019-07-31
    Publishing country China
    Document type Editorial ; Comment
    ZDB-ID 2573571-8
    ISSN 2077-6624 ; 2072-1439
    ISSN (online) 2077-6624
    ISSN 2072-1439
    DOI 10.21037/jtd.2019.05.57
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  10. Book ; Online: A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy

    Dai, Enyan / Cui, Limeng / Wang, Zhengyang / Tang, Xianfeng / Wang, Yinghan / Cheng, Monica / Yin, Bing / Wang, Suhang

    2023  

    Abstract: Graph Neural Networks (GNNs) have achieved great success in modeling graph-structured data. However, recent works show that GNNs are vulnerable to adversarial attacks which can fool the GNN model to make desired predictions of the attacker. In addition, ... ...

    Abstract Graph Neural Networks (GNNs) have achieved great success in modeling graph-structured data. However, recent works show that GNNs are vulnerable to adversarial attacks which can fool the GNN model to make desired predictions of the attacker. In addition, training data of GNNs can be leaked under membership inference attacks. This largely hinders the adoption of GNNs in high-stake domains such as e-commerce, finance and bioinformatics. Though investigations have been made in conducting robust predictions and protecting membership privacy, they generally fail to simultaneously consider the robustness and membership privacy. Therefore, in this work, we study a novel problem of developing robust and membership privacy-preserving GNNs. Our analysis shows that Information Bottleneck (IB) can help filter out noisy information and regularize the predictions on labeled samples, which can benefit robustness and membership privacy. However, structural noises and lack of labels in node classification challenge the deployment of IB on graph-structured data. To mitigate these issues, we propose a novel graph information bottleneck framework that can alleviate structural noises with neighbor bottleneck. Pseudo labels are also incorporated in the optimization to minimize the gap between the predictions on the labeled set and unlabeled set for membership privacy. Extensive experiments on real-world datasets demonstrate that our method can give robust predictions and simultaneously preserve membership privacy.
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Cryptography and Security
    Subject code 006
    Publishing date 2023-06-14
    Publishing country us
    Document type Book ; Online
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