Tetralogy of Fallot (TOF) is the commonest type of cyanotic congenital heart disease which accounts for 10% of all congenital heart disease. Delay in surgical treatment leads to polycythaemia, cerebral abscess, thrombotic episodes etc. Corrective surgery in a case with cerebral abscess always has risk of intracranial hemorrhage during bypass1. We are hereby reporting a case of TOF who had multiple cerebral abscess managed with burr hole operation and extra ventricular drainage. Later 5 coronary stents were placed in Right Ventricular Outflow Tract (RVOT) to Main Pulmonary Artery (MPA) to overcome infundibular and valvular stenosis and thus reducing right to left shunt and cyanosis. This is the first ever palliation with RVOT stenting in a case of Double Outlet Right Ventricle (DORV), Ventricular Septal Defect (VSD), Pulmonary Stenosis (PS) with cerebral abscess where surgery was contraindicated at that time and patient condition was unstable. Later on she had bidirectional Glenn shunt on 8th December 2015 by Saudi charity team.

Nowadays, the healthcare problem is one of the major crises in many parts of the world, especially the COVID-19 pandemic has exacerbated this to a greater extent. Many developing countries with inadequate healthcare systems are suffering greatly from this crisis to provide proper medical services. The reasons are the insufficient number of healthcare providers, costs of medical tests and equipment, lack of accessible points of care and data analysis, and lack of sufficient online healthcare facilities. However, research on the benefits of establishing e-health platforms to strengthen the conventional public-health system is limited-most of the research targets patients in specific disease groups. This paper focuses on an approach for designing a healthcare social media platform for services provisioning, consuming, enabling patients to find an alternate source of healthcare advice, and then building a collaborative health community for all kinds of people. Its usability and applicability have been experimented with as a prototype on Android-based smartphone devices. The results show six features and benefits that are distinct from existing approaches in the literature. In addition, the approach will be considered an affordable alternative to conventional healthcare in case of emergency treatment.Povzetek: Razvita je kolaborativna zdravstvena platforma na Androidu za posredovanje informacij in sodelovanje pri reševanju zdravstvenih težav.

The ubiquitous use of social media has enabled many people, including religious scholars and priests, to share their religious views. Unfortunately, exploiting people's religious beliefs and practices, some extremist groups intentionally or unintentionally spread religious hatred among different communities and thus hamper social stability. This paper aims to propose an abusive behavior detection approach to identify hatred, violence, harassment, and extremist expressions against people of any religious belief on social media. For this, first religious posts from social media users' activities are captured and then the abusive behaviors are identified through a number of sequential processing steps. In the experiment, Twitter has been chosen as an example of social media for collecting dataset of six major religions in English Twittersphere. In order to show the performance of the proposed approach, five classic classifiers on n-gram TF-IDF model have been used. Besides, Long Short-term Memory (LSTM) and Gated Recurrent Unit (GRU) classifiers on trained embedding and pre-trained GloVe word embedding models have been used. The experimental result showed 85% accuracy in terms of precision. However, to the best of our knowledge, this is the first work that will be able to distinguish between hateful and non-hateful contents in other application domains on social media in addition to religious context.