Comprehensive audit of gastrointestinal endoscopy adverse events: Emphasizing quality indicators and economic impact with the AIG-AGREE modification.

This study aimed to conduct a clinical audit of adverse events (AEs) arising from gastrointestinal endoscopy, utilizing the AGREE classification for AEs and establishing its correlation with the ASGE classification. This study further integrated the economic repercussions of AEs into the AGREE classification through the AIG-AGREE modification. A prospective observational study was conducted at the Asian Institute of Gastroenterology, Hyderabad, India, from July 1, 2021, to December 31, 2021.

Development of renewable energy fed three-level hybrid active filter for EV charging station load using Jaya grey wolf optimization.

This work develops a hybrid active power filter (HAPF) in this article to operate in conjunction with the energy storage system (ESS), wind power generation system (WPGS), and solar energy system (SES). It employs three level shunt voltage source converters (VSC) connected to the DC-bus. Optimization of the gain values of the fractional-order proportional integral derivative controller (FOPIDC) and parameter values of the HAPF is achieved using the Jaya grey wolf hybrid algorithm (GWJA).

Breast Masses Detection and Segmentation in Full-Field Digital Mammograms using Unified Convolution Neural Network.

Breast Cancer has been the primary reason for mortality in women of age between twenties and sixties worldwide; moreover early detection and treatment provides patients to get absolute treatment and decrease the mortality rate. Furthermore, recent research indicates that most experienced physicians have plenty of limitations, hence the plethora of work has been carried out to develop an automated mechanism of segmentation and classification of affected area and type of cancer; however, it is still considered to be highly challenging due to the variability of tumor in shape, low signal to noise ratio, shape, size and location of tumor. Furthermore, mammographic mass segmentation and detection are performed as a separate task and a convolution neural network is a highly adopted architecture for the same.

Autonomous service for managing real time notification in detection of COVID-19 virus.

In today's world, the most prominent public issue in the field of medicine is the rapid spread of viral sickness. The seriousness of the disease lies in its fast spreading nature. The main aim of the study is the proposal of a framework for the earlier detection and forecasting of the COVID-19 virus infection amongst the people to avoid the spread of the disease across the world by undertaking the precautionary measures.

A comparative study of perioperative techniques to attain negative margins and spare healthy breast tissue in breast conserving surgery.

Background And Aim: Traditionally lumpectomy as a part of breast-conserving surgery (BCS) is performed by palpation-guided method leading to positive margins and large excision volumes. There is no evidence suggesting that wide margin excisions decrease intra-breast tumour recurrence. Various perioperative techniques are used for margin assessment.