Publications by authors named "M Moghbel"

This research presents a bibliometric analysis of articles predicting crop yield using machine learning methods. While several systematic review articles exist, a comprehensive bibliometric analysis illustrating the knowledge structure and research trends, along with collaboration networks among authors, institutions, and countries in this field, has not been conducted. The study focused on 826 articles published over a 32-year period (1992 to 2023) and revealed a significant increase in publications, particularly in recent years.

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Atmospheric conditions in any place can affect people's health. In recent years, researchers have focused on heat stress and its effect on the exacerbation of some diseases. The main objective of this study is to identify the bioclimatic conditions and its relationship with the admission rate of cardiovascular patients in of Tabriz city.

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Background: Antiphospholipid antibody (aPL) syndrome (APS) is an autoimmune disease characterized by the presence of antiphospholipid antibodies and thromboembolic or pregnancy complications. Although cryptic epitope R39-R43 belonging to beta-2-glycoprotein 1 (β2GP1) has been identified as the main antigenic determinant for aPLs, we have recently demonstrated that the epitope is a motif determined by the polarity, rather than by the sequence or charge of amino acids.

Objective: In the present study, we wanted to identify the association of residues needed to obtain the highest aPL affinity.

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Specialized inferior vena cava (IVC) filter referral centers can achieve improved retrieval outcomes, potentially facilitating complex retrievals after long filter dwell times. The purpose of this study was to determine the success rate of complex IVC filter retrievals at a large specialized IVC filter referral center and to identify predictors of adverse events during complex retrievals. This retrospective study included patients who underwent complex IVC filter retrieval from March 2014 to June 2018 at a large regional health system with specialized complex retrieval referral centers and interventional radiologists with expertise in such procedures.

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Article Synopsis
  • The study examines a novel AI algorithm designed to improve the detection of pulmonary nodules on chest radiographs, which are often missed by traditional methods. !* -
  • Researchers used 100 chest images from patients to test the AI's effectiveness, comparing its performance with that of trained radiologists in both unaided and AI-assisted modes. !* -
  • Results showed that the AI-enhanced interpretation increased detection accuracy of lung nodules by 6.4%, suggesting that AI tools could significantly aid radiologists in identifying early lung cancers. !*
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