Evaluation of chronic hepatitis B patients who voluntarily discontinued oral antiviral therapy: is there an answer to the controversial topic?

Objective: The uncertain treatment duration for nucleos(t)ide analogues (NA) used in the treatment of chronic hepatitis B (CHB) is an important problem for both patients and physicians. The aim of this study was to evaluate the determinants of virologic relapse (VR) and the optimum time of treatment discontinuation in the follow-up of CHB patients who voluntarily discontinued treatment after virological suppression was achieved under NA use.

Methods: Data from 138 patients from 11 centers were included in this registry-based study.

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF.

Evaluation of kidney function tests in HIV-positive patients receiving combined antiretroviral therapy.

Introduction: Human immunodeficiency virus is a chronic infection that attacks the immune system of the human body, particularly CD4 T lymphocytes. Combined antiretroviral therapies are highly effective in virological suppression of human immunodeficiency virus infection. It has been shown that some retroviral therapies have a higher nephrotoxicity potential.

Occult hepatitis B infection in Turkish HIV-infected patients: A multicentre, retrospective, cross-sectional study, Schindler study.

Objective: Occult hepatitis B infection (OHBI) appears to have a higher prevalence in populations at high risk for hepatitis B virus (HBV) infection with concomitant liver disease. The aim was to assess the prevalence of OHBI in a sample of human immunodeficiency virus -1 positive and HBV surface antigen-negative (HIV-1+/HBsAg-) Turkish patients.

Methods: Ten centres in Turkey were included in the study.

Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review.

Deep learning models have become a popular mode to classify electrocardiogram (ECG) data. Investigators have used a variety of deep learning techniques for this application. Herein, a detailed examination of deep learning methods for ECG arrhythmia detection is provided.