Arvind rao biography template

  • UK Arvind Rao's 3 research works with 227 citations, including: A Novel Attribute-Based Symmetric Multiple Instance Learning for Histopathological Image.
  • Arvind UK Rao. University of Michigan.
  • The thesis will cover the topic of guided fuzzing techniques, specifically fuzzing of system calls like open, close, mprotect, mmap, mount .
  • Linux Kernel Custom Call Fuzzing

    RAO, Arvind. Linux Kernel Usage Call Fuzzing. Online. Master's thesis. Brno: Masaryk Campus, Faculty elect Informatics. 2019. Available from: https://is.muni.cz/th/r82kv/.

    RAO, Arvind. \textit{Linux Nut System Buyingoff Fuzzing}. On the net. Master's argument. Brno: Masaryk University, Authorization of Science. 2019. Lean from: https://is.muni.cz/th/r82kv/.

    RAO, Arvind. <i>Linux Kernel Usage Call Fuzzing</i>. Online. Master's thesis. Brno: Masaryk College, Faculty garbage Informatics. 2019. Available from: https://is.muni.cz/th/r82kv/.

    @MastersThesis{Rao2019thesis, Creator = "Rao, Arvind", Designation = "Linux Kernel Shade Call Fuzzing [online]", Twelvemonth = "2019 [cit. 2025-02-24]", TYPE = "Master's thesis", SCHOOL = "Masaryk Academia, Faculty collide Informatics, Brno", NOTE = "SUPERVISOR : Petr Švenda", URL = "https://is.muni.cz/th/r82kv/", }

    @MastersThesis{Rao2019thesis, Creator = {Rao, Arvind}, Give a call = {Linux Kernel Formula Call Fuzzing}, YEAR = {2019}, Imitate = {Master's thesis}, Shop = {Masaryk University, Aptitude of Informatics}, LOCATION = {Brno}, Superintendent = {Petr Švenda}, Twist and turn = {https://is.muni.cz/th/r82kv/}, URL_DATE = {2025-02-24}, }

    {{Citace kvalifikační práce  | příjmení = Rao  | jméno = Arvind  |

  • arvind rao biography template
  • Dr. Kamini Arvind Rao

    Director

    47 Years of Experience

    Gynecologist and Obstetrician, IVF Specialist

    MBBS, DGO, Diploma, DCH, MRCOG, FRCOG, Fellowship, PGDMLS, FNAMS, FICOG

    Reg. No.:16231, Karnataka Medical Council

    Milann Fertility Centre, J P Nagar, Bangalore

    English, Hindi, Kannada

    Consultation Fee ₹ 900

    Book an Appointment

    About Dr. Kamini Arvind Rao

    • Dr. Kamini A. Rao is one of India's best Gynecologists and IVF Specialists.
    • She has over 47 years of experience in treating various gynecological disorders and assisted reproductive technology.
    • Her areas of expertise include infertility, assisted reproduction techniques, andrology, uterine abnormalities and their management, reproductive and child health, genetics and fetal medicine, prenatal diagnosis, fetal surgery, and molecular biology.
    • Throughout her outstanding career in reproductive medicine, Dr. Kamini Rao has specialized in reproductive endocrinology, ovarian physiology, and assisted reproductive technology.
    • Dr. Rao was awarded the prestigious Padma Shri in 2014 and has received numerous other honors, including the Karnataka State Award, Vidya Ratan Award, and lifetime achievement honors from various medical associations.
    • Her early achievements include:
      • Pioneering India's first SIFT (Sem

        Association of graph-based spatial features with overall survival status of glioblastoma patients

        Data availability

        The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

        References

        1. Johnson, D. R. & O’Neill, B. P. Glioblastoma survival in the United States before and during the temozolomide era. J. Neuro-Oncol.107, 359–364. https://doi.org/10.1007/S11060-011-0749-4 (2012).

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        2. Sathornsumetee, S. et al. Molecularly targeted therapy for malignant glioma. Cancer110, 13–24. https://doi.org/10.1002/cncr.22741 (2007).

          ArticlePubMed Google Scholar

        3. Brown, N. F. et al. Survival outcomes and prognostic factors in glioblastoma. Cancers (Basel)14. https://doi.org/10.3390/cancers14133161 (2022).

        4. Assefa, D. et al. Robust texture features for response monitoring of glioblastoma multiforme on T1-weighted and T2-FLAIR MR images: A preliminary investigation in terms of identification and segmentation. Med. Phys.37, 1722–1736 (2010).

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        5. Agner, S. C. et al. Textural kinetics: A novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification. J. Digit. Imaging24, 446–463. https://doi.org/10.