We studied efficacy ofsetegis in different doses for therapy of lower urinary tract symptoms in patients after transvesical adenomectomy (TVAE). The analysis of case histories of 41 patients after open TVPE for prostatic adenoma has shown that setegis (terazosin) is effective in therapy of urinary bladder overactivity which is present in the majority of patients after TVAE. Compared to the controls, terazosin-treated patients improved urination more noticeably. Thus, alpha-adrenoblocker segetis is effective and safe in therapy of imperative voiding disorders with symptoms of urgent incontinence in patients after TVAE. Use of this drug can significantly contribute to successful postoperative rehabilitation of postadenomectomy patients. Setegis can be recommended for wide clinical practice.
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CPT Pharmacometrics Syst Pharmacol
October 2024
Pharmacology & Toxicology, Inserm, U 1248, University of Limoges, CHU Limoges, Limoges, France.
The use of synthetic data in pharmacology research has gained significant attention due to its potential to address privacy concerns and promote open science. In this study, we implemented and compared three synthetic data generation methods, CT-GAN, TVAE, and a simplified implementation of Avatar, for a previously published pharmacogenetic dataset of 253 patients with one measurement per patient (non-longitudinal). The aim of this study was to evaluate the performance of these methods in terms of data utility and privacy trade off.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2023
An emerging area in data science that has lately gained attention is the virtual population (VP) and synthetic data generation. This field has the potential to significantly affect the healthcare industry by providing a means to augment clinical research databases that have a shortage of subjects. The current study provides a comparative analysis of five distinct approaches for creating virtual data populations from real patient data.
View Article and Find Full Text PDFSci Rep
September 2023
Department of Emergency Medicine, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
The triage process in emergency departments (EDs) relies on the subjective assessment of medical practitioners, making it unreliable in certain aspects. There is a need for a more accurate and objective algorithm to determine the urgency of patients. This paper explores the application of advanced data-synthesis algorithms, machine learning (ML) algorithms, and ensemble models to predict patient mortality.
View Article and Find Full Text PDFComput Biol Med
November 2022
Department of Computer Science, National University of Computer and Emerging sciences (NUCES), Lahore, Pakistan. Electronic address:
Acute Pancreatitis (AP) is the inflammation of the pancreas that can be fatal or lead to further complications based on the severity of the attack. Early detection of AP disease can help save lives by providing utmost care, rigorous treatment, and better resources. In this era of data and technology, instead of relying on manual scoring systems, scientists are employing advanced machine learning and data mining models for the early detection of patients with high chances of mortality.
View Article and Find Full Text PDFBME Front
April 2022
Department of Computer Science, University of Rochester, Rochester, USA.
. We adopt a deep learning model for bone osteolysis prediction on computed tomography (CT) images of murine breast cancer bone metastases. Given the bone CT scans at previous time steps, the model incorporates the bone-cancer interactions learned from the sequential images and generates future CT images.
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