Association of mammographic and sonographic findings with prognostic molecular factors and hormone receptor expression in malignant breast lesions.

Background: The aim of this study was to determine whether mammographic and sonographic features of malignant breast lesions are correlated with tumor histologic grade, hormonal receptor, human epidermal growth factor receptor 2 (HER2), and Ki-67 status.

Materials And Methods: In this retrospective study, imaging and histopathological findings of 187 biopsy-proven breast cancer cases from November 2019 to February 2021 were reviewed. The Chi-square test was used to examine the potential correlation between mammographic and sonographic characteristics with histopathological features such as hormonal receptor, HER2 status, Ki-67 labeling index, and histological grade.

A rare presentation of primary cardiac myxofibrosarcoma: Case report and literature review.

Background: Primary cardiac myxofibrosarcoma is a rare and aggressive malignancy, with the majority of approaching strategies relying on case reports. This article provides insights into its diagnosis and treatment.

Case Presentation: This paper presents the case of a 40-year-old man with sudden onset hemoptysis, leading to the diagnosis of primary cardiac myxofibrosarcoma.

Biased Deep Learning Methods in Detection of COVID-19 Using CT Images: A Challenge Mounted by Subject-Wise-Split ISFCT Dataset.

Accurate detection of respiratory system damage including COVID-19 is considered one of the crucial applications of deep learning (DL) models using CT images. However, the main shortcoming of the published works has been unreliable reported accuracy and the lack of repeatability with new datasets, mainly due to slice-wise splits of the data, creating dependency between training and test sets due to shared data across the sets. We introduce a new dataset of CT images (ISFCT Dataset) with labels indicating the subject-wise split to train and test our DL algorithms in an unbiased manner.