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  1. Book ; Online: Network Bioscience, 2nd Edition

    Pellegrini, Marco / Antoniotti, Marco / Mishra, Bud / Antoniotti, Marco

    2020  

    Keywords Science: general issues ; Medical genetics ; systems biology ; network science ; network biology ; cancer networks ; hypothesis generation and verification ; computational biology
    Size 1 electronic resource (270 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021230843
    ISBN 9782889636501 ; 288963650X
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online: Network Bioscience

    Pellegrini, Marco / Antoniotti, Marco / Mishra, Bhubaneswar / Antoniotti, Marco

    2020  

    Keywords Science: general issues ; Medical genetics ; systems biology ; network science ; network biology ; cancer networks ; hypothesis generation and verification ; computational biology
    Size 1 electronic resource (270 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021230842
    ISBN 9782889632893 ; 288963289X
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Article ; Online: Accurate prognosis for localized prostate cancer through coherent voting networks with multi-omic and clinical data.

    Pellegrini, Marco

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 7875

    Abstract: Localized prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing stratifications of patients into risk classes remarkably challenging. In particular, it is ... ...

    Abstract Localized prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing stratifications of patients into risk classes remarkably challenging. In particular, it is important an early detection and discrimination of the indolent forms of the disease, from the aggressive ones, requiring post-surgery closer surveillance and timely treatment decisions. This work extends a recently developed supervised machine learning (ML) technique, called coherent voting networks (CVN) by incorporating a novel model-selection technique to counter the danger of model overfitting. For the challenging problem of discriminating between indolent and aggressive types of localized prostate cancer, accurate prognostic prediction of post-surgery progression-free survival with a granularity within a year is attained, improving accuracy with respect to the current state of the art. The development of novel ML techniques tailored to the problem of combining multi-omics and clinical prognostic biomarkers is a promising new line of attack for sharpening the capability to diversify and personalize cancer patient treatments. The proposed approach allows a finer post-surgery stratification of patients within the clinical high-risk category, with a potential impact on the surveillance regime and the timing of treatment decisions, complementing existing prognostic methods.
    MeSH term(s) Male ; Humans ; Multiomics ; Prostatic Neoplasms/diagnosis ; Prostatic Neoplasms/surgery ; Prognosis ; Biomarkers
    Chemical Substances Biomarkers
    Language English
    Publishing date 2023-05-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-35023-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Editorial: Network bioscience Volume II.

    Antoniotti, Marco / Mishra, Bud / Pellegrini, Marco

    Frontiers in genetics

    2023  Volume 14, Page(s) 1256025

    Language English
    Publishing date 2023-07-26
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2023.1256025
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling.

    Pellegrini, Marco

    Scientific reports

    2021  Volume 11, Issue 1, Page(s) 14645

    Abstract: For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is hard, ...

    Abstract For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is hard, due to the heterogeneous nature of the disease. We devised a methodology for predicting 5-years survival based on the new machine learning paradigm of coherent voting networks, with improved accuracy over state-of-the-art prediction methods. The 'coherent voting communities' metaphor provides a certificate justifying the survival prediction for an individual patient, thus facilitating its acceptability in practice, in the vein of explainable Artificial Intelligence. The method we propose is quite flexible and applicable to other types of cancer.
    MeSH term(s) Artificial Intelligence ; Biomarkers, Tumor/analysis ; Biomarkers, Tumor/genetics ; Breast Neoplasms/genetics ; Breast Neoplasms/mortality ; Breast Neoplasms/pathology ; Breast Neoplasms/therapy ; Chemotherapy, Adjuvant/statistics & numerical data ; Female ; Gene Expression Profiling/statistics & numerical data ; Gene Expression Regulation, Neoplastic/drug effects ; Gene Regulatory Networks/drug effects ; Humans ; Machine Learning ; Mastectomy/statistics & numerical data ; Microarray Analysis ; Neoplasm Recurrence, Local/diagnosis ; Neoplasm Recurrence, Local/genetics ; Neoplasm Recurrence, Local/mortality ; Neoplasm Recurrence, Local/prevention & control ; Neural Networks, Computer ; Predictive Value of Tests ; Prognosis ; Survival Analysis ; Transcriptome/drug effects
    Chemical Substances Biomarkers, Tumor
    Language English
    Publishing date 2021-07-19
    Publishing country England
    Document type Journal Article ; Validation Study
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-021-94243-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling

    Marco Pellegrini

    Scientific Reports, Vol 11, Iss 1, Pp 1-

    2021  Volume 15

    Abstract: Abstract For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient ...

    Abstract Abstract For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is hard, due to the heterogeneous nature of the disease. We devised a methodology for predicting 5-years survival based on the new machine learning paradigm of coherent voting networks, with improved accuracy over state-of-the-art prediction methods. The ’coherent voting communities’ metaphor provides a certificate justifying the survival prediction for an individual patient, thus facilitating its acceptability in practice, in the vein of explainable Artificial Intelligence. The method we propose is quite flexible and applicable to other types of cancer.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  7. Article ; Online: Reply.

    Giannaccare, Giuseppe / Pellegrini, Marco / Scorcia, Vincenzo

    Cornea

    2023  Volume 42, Issue 10, Page(s) e19–e20

    Language English
    Publishing date 2023-07-19
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 604826-2
    ISSN 1536-4798 ; 0277-3740
    ISSN (online) 1536-4798
    ISSN 0277-3740
    DOI 10.1097/ICO.0000000000003351
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1790: Show issues Location:
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    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: Re: Singh et al.: Vaccine-associated uveitis following COVID-19 vaccination: vaccine adverse event reporting system database analysis (Ophthalmology. 2023;130:179-186).

    Pellegrini, Marco / Yu, Angeli Christy

    Ophthalmology

    2023  Volume 130, Issue 4, Page(s) e17–e18

    MeSH term(s) Humans ; COVID-19/prevention & control ; COVID-19 Vaccines/adverse effects ; Uveitis/diagnosis ; Uveitis/etiology ; Vaccination/adverse effects ; Vaccines
    Chemical Substances COVID-19 Vaccines ; Vaccines
    Language English
    Publishing date 2023-01-07
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 392083-5
    ISSN 1549-4713 ; 0161-6420
    ISSN (online) 1549-4713
    ISSN 0161-6420
    DOI 10.1016/j.ophtha.2022.11.023
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Ul II Zs.83: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 533: Show issues

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  9. Article: The Short and Brave Life of Gaetano Perusini: A Tribute to His Role in Shaping Neuroscience.

    Pellegrini, Francesco / Mutali, Musa / Zeppieri, Marco

    Cureus

    2024  Volume 16, Issue 2, Page(s) e54240

    Abstract: Gaetano Perusini was an early enigma in neuroscience. In an age where myths and religion still held tightly to medical knowledge, Dr. Perusini was a trailblazer, inventor, and decorated forerunner. Born in Udine, worshiped in Italy, educated across ... ...

    Abstract Gaetano Perusini was an early enigma in neuroscience. In an age where myths and religion still held tightly to medical knowledge, Dr. Perusini was a trailblazer, inventor, and decorated forerunner. Born in Udine, worshiped in Italy, educated across Europe, published all over the western hemisphere, and taken away from us during a time of worldwide strife, his story continues to fascinate us today. This is a short chronicle of the major events in his life that also celebrates his widely acclaimed influence on understanding Alzheimer's disease.
    Language English
    Publishing date 2024-02-15
    Publishing country United States
    Document type Editorial
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.54240
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Descemet Membrane Epiretinal Graft for Refractory Full-Thickness Macular Hole.

    Pellegrini, Marco / Mura, Marco / Yu, Angeli Christy / Spena, Rossella / Ruzza, Alessandro / Ponzin, Diego / Busin, Massimo / Bovone, Cristina

    Ophthalmology. Retina

    2024  

    Language English
    Publishing date 2024-03-15
    Publishing country United States
    Document type Journal Article
    ISSN 2468-6530
    ISSN (online) 2468-6530
    DOI 10.1016/j.oret.2024.03.011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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