Impact of Obesity on Clinical Presentation and Surgical Outcomes in Patients with Benign Prostate Hyperplasia Receiving Greenlight Laser Prostatectomy.

Objective: To investigate the impact of body mass index (BMI) on preoperative characteristics, lower urinary tract symptoms (LUTS), intraoperative variables, surgical outcomes and postoperative complications.

Methods: This is a retrospective observational study including 891 benign prostate hyperplasia (BPH) patients who underwent GreenLight Laser photoselective vaporization of the prostate (PVP) between 2014 and 2020. Clinical characteristics, uroflowmetry parameters, and surgery related parameters were extracted from electronic health records.

Combining Artificial Intelligence and Simplified Image Processing for the Automatic Detection of Mycobacterium tuberculosis in Acid-fast Stain : A Cross-institute Training and Validation Study.

Tuberculosis (TB) poses a significant health threat in Taiwan, necessitating efficient detection methods. Traditional screening for acid-fast positive bacilli in acid-fast stain is time-consuming and prone to human error due to staining artifacts. To address this, we present an automated TB detection platform leveraging deep learning and image processing.

A Single-Institute Experience with C-ros Oncogene 1 Translocation in Non-Small Cell Lung Cancers in Taiwan.

(1) Background: The C-ros oncogene 1 (ROS1) gene translocation is an important biomarker for selecting patients for crizotinib-targeted therapy. The aim of this study was to understand the incidence, diagnostic algorithm, clinical course and objective response to crizotinib in ROS1 translocated lung non-small cell lung cancers (NSCLCs) in Taiwan. (2) Methods: First, we retrospectively studied the ROS1 status in 100 NSCLC samples using break-apart fluorescent in situ hybridization (FISH) and immunohistochemical (IHC) staining to establish a diagnostic algorithm.

End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model.

Background: The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future renal outcome. However, its assessment by pathologists lacks good agreement. The aim of this study is to construct a machine learning-based model that enables automatic and reliable assessment of interstitial fibrosis in human kidney biopsies.

Safety and Effectiveness of Direct Oral Anticoagulants vs. Warfarin in Patients With Atrial Fibrillation and Endoscopy-Diagnosed Peptic Ulcer.

Patients with active peptic ulcer (PU) were excluded from direct oral anticoagulant (DOAC) trials for stroke prevention in patients with atrial fibrillation (AF). This study evaluated the safety and effectiveness of DOACs in AF patients with active, inactive and no peptic ulcer (PU). This study accessed electronic medical records from January 1, 2009 to May 31, 2019 at a multi-center healthcare provider in Taiwan and involved 2,955 AF patients who had undergone esophagogastroduodenoscopy ≤ 1 year before anticoagulation.

Glomerular disease classification and lesion identification by machine learning.

Background: Classification of glomerular diseases and identification of glomerular lesions require careful morphological examination by experienced nephropathologists, which is labor-intensive, time-consuming, and prone to interobserver variability. In this regard, recent advance in machine learning-based image analysis is promising.

Methods: We combined Mask Region-based Convolutional Neural Networks (Mask R-CNN) with an additional classification step to build a glomerulus detection model using human kidney biopsy samples.

Preliminary study of non-invasive shock wave treatment of capsular contracture after breast implant: animal model.

The incidence rate of capsular contracture after breast implant is about 8% to 12%. Patients would feel extremely uncomfortable after scar formation. Administering oral medications (such as vitamin E and Zafirlukast tablets, etc.