Distribution of Aeration and Pulmonary Blood Volume in Healthy, ARDS and COVID-19 Lungs: A Dual-Energy Computed Tomography Retrospective Cohort Study.

Rationale And Objectives: Few reports have studied lung aeration and perfusion in normal lungs, COVID-19, and ARDS from other causes (NC-ARDS) using dual-energy computed tomography pulmonary angiograms (DE-CTPA). To describe lung aeration and blood-volume distribution using DE-CTPAs of patients with NC-ARDS, COVID-19, and controls with a normal DE-CTPA ("healthy lungs"). We hypothesized that each of these conditions has unique ranges of aeration and pulmonary blood volumes.

Foveal Contour: Presence versus Complete Absence as a Prognostic Factor in Epiretinal Membrane Surgery.

Introduction: The study explains the presence versus complete absence of the foveal contour on optical coherence tomography (OCT) image as predictor of improvement in visual acuity (VA) following epiretinal membrane removal surgery.

Methods: We conducted a retrospective observational study in which 100 eyes that underwent vitrectomy for epiretinal membrane, with preoperative and postoperative VA and OCT, were analyzed. The study population was categorized into four groups based on the preoperational presence of a foveal contour and an intraocular lens implantation.

COVID-19 classification of X-ray images using deep neural networks.

Objectives: In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in diagnosis and monitoring of patients with COVID-19. We propose a deep learning model for detection of COVID-19 from CXRs, as well as a tool for retrieving similar patients according to the model's results on their CXRs. For training and evaluating our model, we collected CXRs from inpatients hospitalized in four different hospitals.