Adjunctive treatment of atopic dermatitis with novel at-home handheld narrow-band UVB phototherapy.

While conventional in-office phototherapy has long been utilized as a successful treatment for atopic dermatitis (AD), it is associated with potential barriers including inconvenience, poor adherence, time and financial expense. In this retrospective study, we examine the efficacy, adherence, and patient-satisfaction of using adjunctive at-home, self-administered phototherapy utilizing a novel handheld narrow-band ultraviolet B (NB-UVB) device for the treatment of refractory mild to severe AD. Included AD patients were initially trained on proper use of the device.

How the Workload and Outcome of Imaging Examinations Changed During the COVID-19 Pandemic Lockdown.

Background: On March 9th, 2020, the Italian government decided to go into lockdown due to the COVID-19 pandemic, which led to changes in the workflow of radiological examinations.

Aims: Aim of the study is to illustrate how the workload and outcome of radiological exams changed in a community hospital during the pandemic.

Methods And Material: The exams performed in the radiology department from March 9th to March 29th, 2020 were retrospectively reviewed and compared to the exams conducted during the same time-period in 2019.

Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning.

Objectives: To evaluate the long-term prognostic value of coronary CT angiography (cCTA)-derived plaque measures and clinical parameters on major adverse cardiac events (MACE) using machine learning (ML).

Methods: Datasets of 361 patients (61.9 ± 10.

Machine Learning and Coronary Artery Calcium Scoring.

Purpose Of Review: To summarize current artificial intelligence (AI)-based applications for coronary artery calcium scoring (CACS) and their potential clinical impact.

Recent Findings: Recent evolution of AI-based technologies in medical imaging has accelerated progress in CACS performed in diverse types of CT examinations, providing promising results for future clinical application in this field. CACS plays a key role in risk stratification of coronary artery disease (CAD) and patient management.

Machine Learning and Deep Neural Networks Applications in Coronary Flow Assessment: The Case of Computed Tomography Fractional Flow Reserve.

Coronary computed tomography angiography (cCTA) is a reliable and clinically proven method for the evaluation of coronary artery disease. cCTA data sets can be used to derive fractional flow reserve (FFR) as CT-FFR. This method has respectable results when compared in previous trials to invasive FFR, with the aim of detecting lesion-specific ischemia.