Impact of the COVID-19 Pandemic on Clinical Findings in Medical Imaging Exams in a Nationwide Israeli Health Organization: Observational Study

Autor: Michal Ozery-Flato, Liat Ein-Dor, Ora Pinchasov, Miel Dabush Kasa, Efrat Hexter, Gabriel Chodick, Michal Rosen-Zvi, Michal Guindy

Publikováno v: JMIR Formative Research, Vol 7, p e42930 (2023)

BackgroundThe outbreak of the COVID-19 pandemic had a major effect on the consumption of health care services. Changes in the use of routine diagnostic exams, increased incidences of postacute COVID-19 syndrome (PCS), and other pandemic-related facto

Externí odkaz: https://doaj.org/article/0fd5c02b2146406cb4fab3e5f7b75ab7

Predictive and Causal Analysis of No-Shows for Medical Exams During COVID-19: A Case Study of Breast Imaging in a Nationwide Israeli Health Organization

Autor: Michal, Ozery-Flato, Ora, Pinchasov, Miel, Dabush-Kasa, Efrat, Hexter, Gabriel, Chodick, Michal, Guindy, Michal, Rosen-Zvi

Publikováno v: AMIA Annu Symp Proc

"No-shows", defined as missed appointments or late cancellations, is a central problem in healthcare systems. It has appeared to intensify during the COVID-19 pandemic and the nonpharmaceutical interventions, such as closures, taken to slow its sprea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::38d7abe2d4d8fc34fee2479feb4a6ac5
https://pubmed.ncbi.nlm.nih.gov/35308922

FuseMedML: a framework for accelerated discovery in machine learning based biomedicine

Autor: Alex Golts, Moshe Raboh, Yoel Shoshan, Sagi Polaczek, Simona Rabinovici-Cohen, Efrat Hexter

Publikováno v: Journal of Open Source Software. 8:4943

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7abba50c6be1ce4dddf46db5e94d71ea
https://doi.org/10.21105/joss.04943

Pre-biopsy Multi-class Classification of Breast Lesion Pathology in Mammograms

Autor: Tal Tlusty, Michal Rosen-Zvi, Mika Amit, Michal Guindy, Ella Barkan, Vesna Resende Barros, David Gruen, Michal Ozery-Flato, Efrat Hexter, Mona Rozin, Tal Arazi

Publikováno v: Machine Learning in Medical Imaging ISBN: 9783030875886
MLMI@MICCAI

Characterization of lesions by artificial intelligence (AI) has been the subject of extensive research. In recent years, many studies demonstrated the ability of convolution neural networks (CNNs) to successfully distinguish between malignant and ben

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::23065141284f2515aedab0f9b4112567
https://doi.org/10.1007/978-3-030-87589-3_29

Radiomics for predicting response to neoadjuvant chemotherapy treatment in breast cancer

Autor: Juha Pajula, Efrat Hexter, Simona Rabinovici-Cohen, Oliver Hijano Cubelos, Xosé M Fernández, Kari Antila, Ami Abutbul, Tal Tlusty, Shaked Perek, Beatriz Grandal Rejo, Abed Khateeb

Publikováno v: Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications
Rabinovici-Cohen, S, Tlusty, T, Abutbul, A, Antila, K, Fernandez, X, Grandal Rejo, B, Hexter, E, Hijano Cubelos, O, Khateeb, A, Pajula, J & Perek, S 2020, Radiomics for predicting response to neoadjuvant chemotherapy treatment in breast cancer . in P-H Chen & T M Deserno (eds), Medical Imaging 2020 : Imaging Informatics for Healthcare, Research, and Applications ., 113181B, International Society for Optics and Photonics SPIE, Progress in Biomedical Optics and Imaging, no. 55, vol. 21, Proceedings of SPIE, vol. 11318, Medical Imaging 2020, Houston, United States, 16/02/20 . https://doi.org/10.1117/12.2551374

Women who are diagnosed with breast cancer are referred to Neoadjuvant Chemotherapy Treatment (NACT) before surgery when treatment guidelines indicate that. Achieving complete response in this treatment is correlated with improved overall survival co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d029d9d1da42ea3155e9dd9bf4fca5b