LIVIVO - Das Suchportal für Lebenswissenschaften

switch to English language
Zurück zur letzten Suche Suchhistorie
Erweiterte Suche

Ihre letzten Suchen

  1. AU="You, Kisung"
  2. AU="Sanjuan, Miguel A" AU="Sanjuan, Miguel A"
  3. AU=Weingarten-Gabbay Shira
  4. AU="Choukr-Allah, Redouane"
  5. AU="Mills, Mary Katherine"
  6. AU="Vajente, G."
  7. AU="Bhatnagar, R.C"
  8. AU="Prasad Sarkale"
  9. AU="Manfredonia, Laura"
  10. AU="Linssen, L"
  11. AU="Davide, Borroni"
  12. AU="Ingrid M. Wentzensen"
  13. AU="A.Parida, "
  14. AU="Zhu, D H"
  15. AU=Ulloa Luis
  16. AU="Böhme, Elisa"
  17. AU=Trko?lu Oya
  18. AU="Levine, Zoe"
  19. AU="Banaszkiewicz, Paul A."
  20. AU="Datrier, Laurence E. H."
  21. AU=Fala Loretta
  22. AU="McGuckin, M M"
  23. AU="Winlaw, David S"
  24. AU="Gökmen, M Refik"
  25. AU="Islam, Tousif"
  26. AU="Szczepanczyk, Marek J"
  27. AU="Boregowda, Siddaraju"
  28. AU="Lomidzew, D."

Suchergebnis

Treffer 1 - 8 von insgesamt 8

Suchoptionen

  1. Artikel ; Online: Geometric learning of functional brain network on the correlation manifold.

    You, Kisung / Park, Hae-Jeong

    Scientific reports

    2022  Band 12, Heft 1, Seite(n) 17752

    Abstract: The correlation matrix is a typical representation of node interactions in functional brain network analysis. The analysis of the correlation matrix to characterize brain networks observed in several neuroimaging modalities has been conducted ... ...

    Abstract The correlation matrix is a typical representation of node interactions in functional brain network analysis. The analysis of the correlation matrix to characterize brain networks observed in several neuroimaging modalities has been conducted predominantly in the Euclidean space by assuming that pairwise interactions are mutually independent. One way to take account of all interactions in the network as a whole is to analyze the correlation matrix under some geometric structure. Recent studies have focused on the space of correlation matrices as a strict subset of symmetric positive definite (SPD) matrices, which form a unique mathematical structure known as the Riemannian manifold. However, mathematical operations of the correlation matrix under the SPD geometry may not necessarily be coherent (i.e., the structure of the correlation matrix may not be preserved), necessitating a post-hoc normalization. The contribution of the current paper is twofold: (1) to devise a set of inferential methods on the correlation manifold and (2) to demonstrate its applicability in functional network analysis. We present several algorithms on the correlation manifold, including measures of central tendency, cluster analysis, hypothesis testing, and low-dimensional embedding. Simulation and real data analysis support the application of the proposed framework for brain network analysis.
    Mesh-Begriff(e) Algorithms ; Brain/diagnostic imaging ; Computer Simulation
    Sprache Englisch
    Erscheinungsdatum 2022-10-22
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-21376-0
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Zusatzmaterialien

    Kategorien

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

  2. Artikel: Parameter estimation and model-based clustering with spherical normal distribution on the unit hypersphere

    You, Kisung / Suh, Changhee

    Computational statistics & data analysis. 2022 July, v. 171

    2022  

    Abstract: In directional statistics, the von Mises-Fisher (vMF) distribution is one of the most basic and popular probability distributions for data on the unit hypersphere. Recently, the spherical normal (SN) distribution was proposed as an intrinsic counterpart ... ...

    Abstract In directional statistics, the von Mises-Fisher (vMF) distribution is one of the most basic and popular probability distributions for data on the unit hypersphere. Recently, the spherical normal (SN) distribution was proposed as an intrinsic counterpart to the vMF distribution by replacing the standard Euclidean norm with the great-circle distance, which is length of the shortest path joining two points on the unit sphere. Focusing on an isotropic version of SN distribution, it is shown that maximum likelihood estimators uniquely exist under mild support conditions. Since no analytic formula are available for the estimation, efficient numerical routines are proposed for parameter estimation. The estimation is considered in a general setting where non-negative weights are assigned to observations. This leads to a more interesting contribution for model-based clustering on the unit hypersphere by finite mixture model with SN distributions. Efficiency of optimization-based estimation procedures and effectiveness of SN mixture model are validated using simulated and real data examples.
    Schlagwörter data analysis ; isotropy ; models ; normal distribution ; probability
    Sprache Englisch
    Erscheinungsverlauf 2022-07
    Erscheinungsort Elsevier B.V.
    Dokumenttyp Artikel
    ZDB-ID 1478763-5
    ISSN 0167-9473
    ISSN 0167-9473
    DOI 10.1016/j.csda.2022.107457
    Datenquelle NAL Katalog (AGRICOLA)

    Volltext online

    Zusatzmaterialien

    Kategorien

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

  3. Artikel ; Online: Evaluating ChatGPT in Medical Contexts: The Imperative to Guard Against Hallucinations and Partial Accuracies.

    Giuffrè, Mauro / You, Kisung / Shung, Dennis L

    Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association

    2023  Band 22, Heft 5, Seite(n) 1145–1146

    Sprache Englisch
    Erscheinungsdatum 2023-10-19
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Letter
    ZDB-ID 2119789-1
    ISSN 1542-7714 ; 1542-3565
    ISSN (online) 1542-7714
    ISSN 1542-3565
    DOI 10.1016/j.cgh.2023.09.035
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Volltext online

    Zusatzmaterialien

    Kategorien

    Verfügbar in ZB MED Köln/Königswinter

    Zs.A 5836: Hefte anzeigen Standort:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

  4. Artikel ; Online: Re-visiting Riemannian geometry of symmetric positive definite matrices for the analysis of functional connectivity.

    You, Kisung / Park, Hae-Jeong

    NeuroImage

    2020  Band 225, Seite(n) 117464

    Abstract: Common representations of functional networks of resting state fMRI time series, including covariance, precision, and cross-correlation matrices, belong to the family of symmetric positive definite (SPD) matrices forming a special mathematical structure ... ...

    Abstract Common representations of functional networks of resting state fMRI time series, including covariance, precision, and cross-correlation matrices, belong to the family of symmetric positive definite (SPD) matrices forming a special mathematical structure called Riemannian manifold. Due to its geometric properties, the analysis and operation of functional connectivity matrices may well be performed on the Riemannian manifold of the SPD space. Analysis of functional networks on the SPD space takes account of all the pairwise interactions (edges) as a whole, which differs from the conventional rationale of considering edges as independent from each other. Despite its geometric characteristics, only a few studies have been conducted for functional network analysis on the SPD manifold and inference methods specialized for connectivity analysis on the SPD manifold are rarely found. The current study aims to show the significance of connectivity analysis on the SPD space and introduce inference algorithms on the SPD manifold, such as regression analysis of functional networks in association with behaviors, principal geodesic analysis, clustering, state transition analysis of dynamic functional networks and statistical tests for network equality on the SPD manifold. We applied the proposed methods to both simulated data and experimental resting state fMRI data from the human connectome project and argue the importance of analyzing functional networks under the SPD geometry. All the algorithms for numerical operations and inferences on the SPD manifold are implemented as a MATLAB library, called SPDtoolbox, for public use to expediate functional network analysis on the right geometry.
    Mesh-Begriff(e) Algorithms ; Connectome/instrumentation ; Data Interpretation, Statistical ; Databases, Factual ; Humans ; Magnetic Resonance Imaging/methods ; Regression Analysis ; Signal Processing, Computer-Assisted
    Sprache Englisch
    Erscheinungsdatum 2020-10-17
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1147767-2
    ISSN 1095-9572 ; 1053-8119
    ISSN (online) 1095-9572
    ISSN 1053-8119
    DOI 10.1016/j.neuroimage.2020.117464
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Volltext online

    Zusatzmaterialien

    Kategorien

    Verfügbar in ZB MED Köln/Königswinter

    Zs.A 3664: Hefte anzeigen Standort:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 7: Hefte anzeigen

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

  5. Buch ; Online: Shape-Preserving Dimensionality Reduction

    Yu, Byeongsu / You, Kisung

    An Algorithm and Measures of Topological Equivalence

    2021  

    Abstract: We introduce a linear dimensionality reduction technique preserving topological features via persistent homology. The method is designed to find linear projection $L$ which preserves the persistent diagram of a point cloud $\mathbb{X}$ via simulated ... ...

    Abstract We introduce a linear dimensionality reduction technique preserving topological features via persistent homology. The method is designed to find linear projection $L$ which preserves the persistent diagram of a point cloud $\mathbb{X}$ via simulated annealing. The projection $L$ induces a set of canonical simplicial maps from the Rips (or \v{C}ech) filtration of $\mathbb{X}$ to that of $L\mathbb{X}$. In addition to the distance between persistent diagrams, the projection induces a map between filtrations, called filtration homomorphism. Using the filtration homomorphism, one can measure the difference between shapes of two filtrations directly comparing simplicial complexes with respect to quasi-isomorphism $\mu_{\operatorname{quasi-iso}}$ or strong homotopy equivalence $\mu_{\operatorname{equiv}}$. These $\mu_{\operatorname{quasi-iso}}$ and $\mu_{\operatorname{equiv}}$ measures how much portion of corresponding simplicial complexes is quasi-isomorphic or homotopy equivalence respectively. We validate the effectiveness of our framework with simple examples.

    Comment: 18 pages, 2 figures
    Schlagwörter Statistics - Machine Learning ; Computer Science - Machine Learning
    Thema/Rubrik (Code) 514
    Erscheinungsdatum 2021-06-03
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

    Volltext online

    Zusatzmaterialien

    Kategorien

    Fernleihe an ZB MED

    Sie können sich den gewünschten Titel als lokale Nutzerin oder lokaler Nutzer von ZB MED direkt an den Standort Köln schicken lassen.

  6. Artikel ; Online: Predicting response to non-selective beta-blockers with liver-spleen stiffness and heart rate in patients with liver cirrhosis and high-risk varices.

    Giuffrè, Mauro / Dupont, Johannes / Visintin, Alessia / Masutti, Flora / Monica, Fabio / You, Kisung / Shung, Dennis L / Crocè, Lory Saveria

    Hepatology international

    2024  

    Abstract: Introduction: Non-selective beta-blockers (NSBB) are used for primary prophylaxis in patients with liver cirrhosis and high-risk varices (HRVs). Assessing therapeutic response is challenging due to the invasive nature of hepatic venous pressure gradient ...

    Abstract Introduction: Non-selective beta-blockers (NSBB) are used for primary prophylaxis in patients with liver cirrhosis and high-risk varices (HRVs). Assessing therapeutic response is challenging due to the invasive nature of hepatic venous pressure gradient (HVPG) measurement. This study aims to define a noninvasive machine-learning based approach to determine response to NSBB in patients with liver cirrhosis and HRVs.
    Methods: We conducted a prospective study on a cohort of cirrhotic patients with documented HRVs receiving NSBB treatment. Patients were followed-up with clinical and elastography appointments at 3, 6, and 12 months after NSBB treatment initiation. NSBB response was defined as stationary or downstaging variceal grading at the 12-month esophagogastroduodenoscopy (EGD). In contrast, non-response was defined as upstaging variceal grading at the 12-month EGD or at least one variceal hemorrhage episode during the 12-month follow-up. We chose cut-off values for univariate and multivariate model with 100% specificity.
    Results: According to least absolute shrinkage and selection operator (LASSO) regression, spleen stiffness (SS) and liver stiffness (LS) percentual decrease, along with changes in heart rate (HR) at 3 months were the most significant predictors of NSBB response. A decrease > 11.5% in SS, > 16.8% in LS, and > 25.3% in HR was associated with better prediction of clinical response to NSBB. SS percentual decrease showed the highest accuracy (86.4%) with high sensitivity (78.8%) when compared to LS and HR. The multivariate model incorporating SS, LS, and HR showed the highest discrimination and calibration metrics (AUROC = 0.96), with the optimal cut-off of 0.90 (sensitivity 94.2%, specificity 100%, PPV 95.7%, NPV 100%, accuracy 97.5%).
    Sprache Englisch
    Erscheinungsdatum 2024-04-25
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2270316-0
    ISSN 1936-0541 ; 1936-0533
    ISSN (online) 1936-0541
    ISSN 1936-0533
    DOI 10.1007/s12072-024-10649-7
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Volltext online

    Zusatzmaterialien

    Kategorien

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

  7. Buch ; Online: Assessing the Usability of GutGPT

    Chan, Colleen / You, Kisung / Chung, Sunny / Giuffrè, Mauro / Saarinen, Theo / Rajashekar, Niroop / Pu, Yuan / Shin, Yeo Eun / Laine, Loren / Wong, Ambrose / Kizilcec, René / Sekhon, Jasjeet / Shung, Dennis

    A Simulation Study of an AI Clinical Decision Support System for Gastrointestinal Bleeding Risk

    2023  

    Abstract: Applications of large language models (LLMs) like ChatGPT have potential to enhance clinical decision support through conversational interfaces. However, challenges of human-algorithmic interaction and clinician trust are poorly understood. GutGPT, a LLM ...

    Abstract Applications of large language models (LLMs) like ChatGPT have potential to enhance clinical decision support through conversational interfaces. However, challenges of human-algorithmic interaction and clinician trust are poorly understood. GutGPT, a LLM for gastrointestinal (GI) bleeding risk prediction and management guidance, was deployed in clinical simulation scenarios alongside the electronic health record (EHR) with emergency medicine physicians, internal medicine physicians, and medical students to evaluate its effect on physician acceptance and trust in AI clinical decision support systems (AI-CDSS). GutGPT provides risk predictions from a validated machine learning model and evidence-based answers by querying extracted clinical guidelines. Participants were randomized to GutGPT and an interactive dashboard, or the interactive dashboard and a search engine. Surveys and educational assessments taken before and after measured technology acceptance and content mastery. Preliminary results showed mixed effects on acceptance after using GutGPT compared to the dashboard or search engine but appeared to improve content mastery based on simulation performance. Overall, this study demonstrates LLMs like GutGPT could enhance effective AI-CDSS if implemented optimally and paired with interactive interfaces.

    Comment: Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2023, December 10, 2023, New Orleans, United States, 11 pages
    Schlagwörter Computer Science - Human-Computer Interaction ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Statistics - Applications
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2023-12-06
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

    Volltext online

    Zusatzmaterialien

    Kategorien

    Fernleihe an ZB MED

    Sie können sich den gewünschten Titel als lokale Nutzerin oder lokaler Nutzer von ZB MED direkt an den Standort Köln schicken lassen.

  8. Artikel ; Online: Single-cell analysis reveals inflammatory interactions driving macular degeneration.

    Kuchroo, Manik / DiStasio, Marcello / Song, Eric / Calapkulu, Eda / Zhang, Le / Ige, Maryam / Sheth, Amar H / Majdoubi, Abdelilah / Menon, Madhvi / Tong, Alexander / Godavarthi, Abhinav / Xing, Yu / Gigante, Scott / Steach, Holly / Huang, Jessie / Huguet, Guillaume / Narain, Janhavi / You, Kisung / Mourgkos, George /
    Dhodapkar, Rahul M / Hirn, Matthew J / Rieck, Bastian / Wolf, Guy / Krishnaswamy, Smita / Hafler, Brian P

    Nature communications

    2023  Band 14, Heft 1, Seite(n) 2589

    Abstract: Due to commonalities in pathophysiology, age-related macular degeneration (AMD) represents a uniquely accessible model to investigate therapies for neurodegenerative diseases, leading us to examine whether pathways of disease progression are shared ... ...

    Abstract Due to commonalities in pathophysiology, age-related macular degeneration (AMD) represents a uniquely accessible model to investigate therapies for neurodegenerative diseases, leading us to examine whether pathways of disease progression are shared across neurodegenerative conditions. Here we use single-nucleus RNA sequencing to profile lesions from 11 postmortem human retinas with age-related macular degeneration and 6 control retinas with no history of retinal disease. We create a machine-learning pipeline based on recent advances in data geometry and topology and identify activated glial populations enriched in the early phase of disease. Examining single-cell data from Alzheimer's disease and progressive multiple sclerosis with our pipeline, we find a similar glial activation profile enriched in the early phase of these neurodegenerative diseases. In late-stage age-related macular degeneration, we identify a microglia-to-astrocyte signaling axis mediated by interleukin-1β which drives angiogenesis characteristic of disease pathogenesis. We validated this mechanism using in vitro and in vivo assays in mouse, identifying a possible new therapeutic target for AMD and possibly other neurodegenerative conditions. Thus, due to shared glial states, the retina provides a potential system for investigating therapeutic approaches in neurodegenerative diseases.
    Mesh-Begriff(e) Humans ; Mice ; Animals ; Macular Degeneration/metabolism ; Retina/metabolism ; Neuroglia/metabolism ; Neurodegenerative Diseases/metabolism ; Single-Cell Analysis
    Sprache Englisch
    Erscheinungsdatum 2023-05-05
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-37025-7
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Zusatzmaterialien

    Kategorien

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

Zum Seitenanfang