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  1. Article ; Online: Cesarean Sections and Family Planning Among Ultra-Orthodox Israeli Jews.

    Arbel, Yuval / Bar-El, Ronen

    Journal of religion and health

    2024  

    Abstract: The elevated frequency of Cesarean sections (C-sections) in OECD countries not only burdens health systems financially but also heightens the risks for mothers and infants. This study explores the feasibility of reducing C-section rates by examining the ... ...

    Abstract The elevated frequency of Cesarean sections (C-sections) in OECD countries not only burdens health systems financially but also heightens the risks for mothers and infants. This study explores the feasibility of reducing C-section rates by examining the Israeli ultra-Orthodox population, noted for its large families and low C-section rates. We analyze birth data from an Israeli hospital, focusing on ultra-Orthodox mothers with husbands who are yeshiva students compared to other mothers. Our findings reveal that all else being equal, mothers married to yeshiva students exhibit a lower likelihood of undergoing a C-section and a higher propensity to seek private medical services to avoid this procedure. This behavior is attributed to their preference for large families and the desire to minimize C-sections, which may restrict the number of possible future pregnancies. These insights underscore the potential effectiveness of initiatives encouraging mothers to opt for vaginal deliveries, thereby reducing healthcare costs and maternal-infant risks.
    Language English
    Publishing date 2024-04-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2017250-3
    ISSN 1573-6571 ; 0022-4197
    ISSN (online) 1573-6571
    ISSN 0022-4197
    DOI 10.1007/s10943-024-02026-3
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  2. Article: Corynebacterium bovis surgical site infection and brain abscess: The first case report and literature review.

    Gabay, Segev / Tene, Yael / Ben-Ami, Ronen / Shapira, Yuval

    IDCases

    2023  Volume 33, Page(s) e01782

    Abstract: Corynebacterium ... ...

    Abstract Corynebacterium bovis
    Language English
    Publishing date 2023-05-08
    Publishing country Netherlands
    Document type Case Reports
    ZDB-ID 2745454-X
    ISSN 2214-2509
    ISSN 2214-2509
    DOI 10.1016/j.idcr.2023.e01782
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  3. Article ; Online: Efficacy of ultraviolet A1 phototherapy for inflammatory, sclerotic and neoplastic dermatological diseases: A 10-year tertiary referral center experience.

    Ronen, Shachar / Ramot, Yuval / Zlotogorski, Abraham / Shreberk-Hassidim, Rony

    Photodermatology, photoimmunology & photomedicine

    2022  Volume 39, Issue 3, Page(s) 256–262

    Abstract: Background: Ultraviolet (UV) A1 phototherapy is considered a beneficial treatment for various inflammatory, sclerotic, malignant, and other skin conditions. However, the available data regarding its efficacy for different indications, the potential side ...

    Abstract Background: Ultraviolet (UV) A1 phototherapy is considered a beneficial treatment for various inflammatory, sclerotic, malignant, and other skin conditions. However, the available data regarding its efficacy for different indications, the potential side effects, and the recommended treatment protocols are sparse.
    Objectives: To assess the efficacy of UVA1 phototherapy and identify correlation between different indications and treatment protocols to response rates.
    Methods: We performed a retrospective study of a cohort of 335 patients treated with UVA1 phototherapy at the Department of Dermatology at Hadassah Medical Center, Jerusalem, Israel, between 2008 and 2018.
    Results: The study population included 163 patients with inflammatory diseases (mainly atopic dermatitis and other types of eczema), 67 patients with sclerotic diseases (morphea and graft versus host disease), nine patients with neoplastic diseases (cutaneous T cell lymphoma), and 188 patients with other cutaneous disorders. Response rates ranged between 85% and 89% across indications, without differences in response rates among the indication groups (p = .941). In a multivariant logistic regression model, increased number of treatments and higher maximal dosages were associated with response to treatment (p < .001). Using ROC analysis, a cut-off of 8 UVA1 phototherapy treatments was chosen as predictive for beneficial response (86.4% sensitivity, 78% specificity). A cut-off of 40 J/cm
    Conclusions: UVA1 phototherapy is an effective treatment for a variety of skin conditions. In most patients, at least eight treatments of a medium-high dosage are required for clinical response.
    MeSH term(s) Humans ; Ultraviolet Therapy/adverse effects ; Retrospective Studies ; Tertiary Care Centers ; Scleroderma, Localized/etiology ; Scleroderma, Localized/pathology ; Treatment Outcome ; Skin Neoplasms/etiology ; Phototherapy
    Language English
    Publishing date 2022-09-13
    Publishing country England
    Document type Journal Article
    ZDB-ID 1028855-7
    ISSN 1600-0781 ; 0108-9684 ; 0905-4383
    ISSN (online) 1600-0781
    ISSN 0108-9684 ; 0905-4383
    DOI 10.1111/phpp.12833
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  4. Article: SORBET: Automated cell-neighborhood analysis of spatial transcriptomics or proteomics for interpretable sample classification via GNN.

    Shimonov, Shay / Cunningham, Joseph M / Talmon, Ronen / Aizenbud, Lilach / Desai, Shruti J / Rimm, David / Schalper, Kurt / Kluger, Harriet / Kluger, Yuval

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Spatially resolved transcriptomics or proteomics data have the potential to contribute fundamental insights into the mechanisms underlying physiologic and pathological processes. However, analysis of these data capable of relating spatial information, ... ...

    Abstract Spatially resolved transcriptomics or proteomics data have the potential to contribute fundamental insights into the mechanisms underlying physiologic and pathological processes. However, analysis of these data capable of relating spatial information, multiplexed markers, and their observed phenotypes remains technically challenging. To analyze these relationships, we developed SORBET, a deep learning framework that leverages recent advances in graph neural networks (GNN). We apply SORBET to predict tissue phenotypes, such as response to immunotherapy, across different disease processes and different technologies including both spatial proteomics and transcriptomics methods. Our results show that SORBET accurately learns biologically meaningful relationships across distinct tissue structures and data acquisition methods. Furthermore, we demonstrate that SORBET facilitates understanding of the spatially-resolved biological mechanisms underlying the inferred phenotypes. In sum, our method facilitates mapping between the rich spatial and marker information acquired from spatial 'omics technologies to emergent biological phenotypes. Moreover, we provide novel techniques for identifying the biological processes that comprise the predicted phenotypes.
    Language English
    Publishing date 2024-01-01
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.12.30.573739
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  5. Article ; Online: Revealing the uterine blood vessel network via virtual pathology.

    Kolatt, Tsafrir S / Shufaro, Yoel / Mashiach, Shlomo / Czernobilsky, Bernard / Aviel-Ronen, Sarit / Apel-Sarid, Liat / Dahan, Mazal / Or, Yuval

    Reproduction & fertility

    2023  

    Abstract: Background: The distribution of the blood vessel network at any point in time in any body tissue, may provide valuable information with regards to the tissue condition and its angiogenesis functionality. The blood vessel three-dimensional network of the ...

    Abstract Background: The distribution of the blood vessel network at any point in time in any body tissue, may provide valuable information with regards to the tissue condition and its angiogenesis functionality. The blood vessel three-dimensional network of the endometrium goes through a process of change over a relatively short period of 4 weeks on average. It is well accepted that this angiogenesis is closely related to the success or failure of the implantation of the embryo Objective and rationale: Our study aims to present a method to follow the three-dimensional evolution of the superficial blood vessel distribution in the endometrium throughout the uterine cycle.
    Method: This method utilizes differences in the observed broadband colors of the blood vessels in order to assess their depth coordinate below the endometrial tissue surface. We implemented the method using microscopic images of fresh, ex-vivo, endometrial samples of different cycle days to obtain the statistical evolution track of the superficial blood vessel population in both human and animal (swine) samples.
    Outcomes: In human samples we observed a systematic and consistent trend in the BV diameter distribution at different tissue depths. We demonstrate that the magnitude of this trend evolves throughout the course of the female cycle.
    Wider implications: This method has the potential to further our understanding of the mechanisms of angiogenesis in tissues other than the endometrium. We propose that this method may also contribute to more precise endometrial dating and may assist in more accurate determination of embryo transfer timing within IVF treatments.
    Language English
    Publishing date 2023-02-01
    Publishing country England
    Document type Journal Article
    ISSN 2633-8386
    ISSN (online) 2633-8386
    DOI 10.1530/RAF-22-0135
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  6. Article ; Online: A new method for endometrial dating using computerized virtual pathology.

    Or, Yuval / Shufaro, Yoel / Mashiach, Shlomo / Czernobilsky, Bernard / Aviel-Ronen, Sarit / Apel-Sarid, Liat / Dahan, Mazal / Kolatt, Tsafrir S

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 21308

    Abstract: Endometrial dating (ED) is the process by which the menstrual cycle day is estimated and is an important tool for the evaluation of uterine status. To date, ED methods remain inaccurate and controversial. We demonstrate how the rise of computerized ... ...

    Abstract Endometrial dating (ED) is the process by which the menstrual cycle day is estimated and is an important tool for the evaluation of uterine status. To date, ED methods remain inaccurate and controversial. We demonstrate how the rise of computerized virtual histology changes the state of affairs and introduce a new ED method. We present the results of a clinical trial where magnified images of ex-vivo endometrial tissue samples were captured at different cycle days, together with measurements of serum hormone levels on the same day. Patient testimonies about their cycle day were also collected. Computerized image analysis, followed by statistical representation of the tissue features, allowed mathematical representation of the cycle day. The samples underwent ED histological assessment, which is currently the ED gold standard. We compared dating results from patient reports, serum hormone levels, and histology to establish their concordance level. We then compared histology-based ED with the new method ED in the secretory phase (i.e. post ovulation). The correlation coefficient between the two resulted in an R = 0.89 with a P-value of P < 10
    MeSH term(s) Female ; Humans ; Endometrium/pathology ; Menstrual Cycle ; Uterus ; Luteal Phase ; Hormones
    Chemical Substances Hormones
    Language English
    Publishing date 2023-12-02
    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/s41598-023-48481-y
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  7. Book ; Online: Social Media and Democracy

    Gradwohl, Ronen / Heller, Yuval / Hillman, Arye

    2022  

    Abstract: We study the ability of a social media platform with a political agenda to influence voting outcomes. Our benchmark is Condorcet's jury theorem, which states that the likelihood of a correct decision under majority voting increases with the number of ... ...

    Abstract We study the ability of a social media platform with a political agenda to influence voting outcomes. Our benchmark is Condorcet's jury theorem, which states that the likelihood of a correct decision under majority voting increases with the number of voters. We show how information manipulation by a social media platform can overturn the jury theorem, thereby undermining democracy. We also show that sometimes the platform can do so only by providing information that is biased in the opposite direction of its preferred outcome. Finally, we compare manipulation of voting outcomes through social media to manipulation through traditional media.
    Keywords Economics - Theoretical Economics ; Computer Science - Computer Science and Game Theory
    Publishing date 2022-06-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: A new method for endometrial dating using computerized virtual pathology

    Yuval Or / Yoel Shufaro / Shlomo Mashiach / Bernard Czernobilsky / Sarit Aviel-Ronen / Liat Apel-Sarid / Mazal Dahan / Tsafrir S. Kolatt

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    2023  Volume 11

    Abstract: Abstract Endometrial dating (ED) is the process by which the menstrual cycle day is estimated and is an important tool for the evaluation of uterine status. To date, ED methods remain inaccurate and controversial. We demonstrate how the rise of ... ...

    Abstract Abstract Endometrial dating (ED) is the process by which the menstrual cycle day is estimated and is an important tool for the evaluation of uterine status. To date, ED methods remain inaccurate and controversial. We demonstrate how the rise of computerized virtual histology changes the state of affairs and introduce a new ED method. We present the results of a clinical trial where magnified images of ex-vivo endometrial tissue samples were captured at different cycle days, together with measurements of serum hormone levels on the same day. Patient testimonies about their cycle day were also collected. Computerized image analysis, followed by statistical representation of the tissue features, allowed mathematical representation of the cycle day. The samples underwent ED histological assessment, which is currently the ED gold standard. We compared dating results from patient reports, serum hormone levels, and histology to establish their concordance level. We then compared histology-based ED with the new method ED in the secretory phase (i.e. post ovulation). The correlation coefficient between the two resulted in an R = 0.89 with a P-value of P < 10–4. The new method, Virtual Pathology Endometrial Dating (VPED), has the benefit of being a real time, in-vivo method that can be repeatedly applied without tissue damage, using a dedicated hysteroscope. One practical use of this method may be the determination of accurate real-time embryo transfer timing in IVF treatments.
    Keywords Medicine ; R ; Science ; Q
    Subject code 630
    Language English
    Publishing date 2023-12-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Book ; Online: GRelPose

    Khatib, Fadi / Margalit, Yuval / Galun, Meirav / Basri, Ronen

    Generalizable End-to-End Relative Camera Pose Regression

    2022  

    Abstract: This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images. Given two images of the same scene captured from different viewpoints, our algorithm predicts the relative rotation and ... ...

    Abstract This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images. Given two images of the same scene captured from different viewpoints, our algorithm predicts the relative rotation and translation between the two respective cameras. Despite recent progress in the field, current deep-based methods exhibit only limited generalization to scenes not seen in training. Our approach introduces a network architecture that extracts a grid of coarse features for each input image using the pre-trained LoFTR network. It subsequently relates corresponding features in the two images, and finally uses a convolutional network to recover the relative rotation and translation between the respective cameras. Our experiments indicate that the proposed architecture can generalize to novel scenes, obtaining higher accuracy than existing deep-learning-based methods in various settings and datasets, in particular with limited training data.
    Keywords Computer Science - Computer Vision and Pattern Recognition
    Subject code 006
    Publishing date 2022-11-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: ManiFeSt

    Cohen, David / Shnitzer, Tal / Kluger, Yuval / Talmon, Ronen

    Manifold-based Feature Selection for Small Data Sets

    2022  

    Abstract: In this paper, we present a new method for few-sample supervised feature selection (FS). Our method first learns the manifold of the feature space of each class using kernels capturing multi-feature associations. Then, based on Riemannian geometry, a ... ...

    Abstract In this paper, we present a new method for few-sample supervised feature selection (FS). Our method first learns the manifold of the feature space of each class using kernels capturing multi-feature associations. Then, based on Riemannian geometry, a composite kernel is computed, extracting the differences between the learned feature associations. Finally, a FS score based on spectral analysis is proposed. Considering multi-feature associations makes our method multivariate by design. This in turn allows for the extraction of the hidden manifold underlying the features and avoids overfitting, facilitating few-sample FS. We showcase the efficacy of our method on illustrative examples and several benchmarks, where our method demonstrates higher accuracy in selecting the informative features compared to competing methods. In addition, we show that our FS leads to improved classification and better generalization when applied to test data.

    Comment: 22 pages, 10 figures
    Keywords Statistics - Machine Learning ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Signal Processing
    Subject code 004
    Publishing date 2022-07-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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