Analysis of Long COVID Phenotypes and their Impact on Mental Health and Daily Functioning: Insights from Twitter

In this study, we conducted an investigation into Long COVID from a user perspective, utilizing Twitter social media data. Prior to analysis, the data underwent preprocessing to obtain raw text per tweet. Our analysis commenced with basic statistical analysis and subsequently expanded to identify characteristic periods for the phenotypes based on dynamic timelines. We also explored the relationships between the phenotypes, as well as the interdependence between phenotypes and geolocation. In the context of this research, an analysis was conducted on a collection of tweets that encompassed the timeframe from March 2020 to March 2022. The dataset consisted of approximately 1.9 million tweets. In order to concentrate on word phrases, extraneous elements such as mentions, emoticons, links, and hashtags were eliminated. Subsequently, a process of lemmatization was performed. For the purpose of reducing the number of distinct phenotypes under investigation and facilitating the presentation of results, the collected data was categorized into five overarching groups: Cardiovascular, Respiratory, Daily Living, Neurological and Mental Health, and Other. The statistical data regarding the most commonly used words by individuals describing their experiences during the Long COVID period are as follows: “Ampicillin” was tweeted 125,295 times, “Death” was tweeted 121,156 times, “Suffer” was tweeted 125,113 times, and “Vaccine” was tweeted 108,968 times. We observe distinct patterns in the emergence of certain phenotypes during this period, particularly in relation to the quality of life. On August 1, 2020, the term “quality of life” was mentioned in only 223 tweets, whereas one year later, during the same month, this phenotype garnered 1,663 tweets. Our findings reveal that the occurrence of Long COVID phenotypes is influenced by both temporal and geographical factors. The analysis shows a clear and notable trend within the dataset. Specifically, it is observed that neurological symptoms, along with symptoms that impede individuals’ daily functioning, exhibit the highest prevalence, particularly during the latter half of the analyzed tweet period. This period corresponds to a time when an increasing number of individuals have recovered from COVID-19 and are reporting their experiences with Long COVID. Notably, fatigue, depression, stress, and anxiety emerge as the most prevalent phenotypes. This scientific investigation of the complex interactions between Long COVID phenotypes, mental health, and the manifestation of diverse symptoms is offering insights into the profound consequences on individuals’ lives. These findings shed light on the significant burden posed by Long COVID and its cascading effects on various aspects of individuals’ well-being and society at large.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

Exploring Changes in Diagnoses during the COVID-19 Era: Comparative Analysis

The healthcare sector is just one of several areas of society that have been significantly impacted by the COVID-19 pandemic. This paper aims to analyze the changes observed in the medical profession’s approach to diagnosing diseases between the pre-pandemic year of 2019 and the pandemic year of 2020. By examining these shifts, we explore how medical professionals have adapted their treatment strategies, leading to modifications in diagnosis for various diseases. Based on our visualization, shown in Figure 1, we observed that the diagnoses of Obstructive Sleep Apnea and End stage renal disease had consistent distributions in both 2019 and 2020. Also we need to mention, the count value for Obstructive Sleep Apnea was higher in 2020, whereas in 2019, the count value was higher for End stage renal disease, showing their representation in each year. We can conclude that the pandemic has resulted in a marked increase in the occurrence of specific diagnoses compared to the previous year, some of them being acute pharyngitis-sore throat (J029), gastro-oesophageal reflux disease (K219) and pure hypercholesterolemia - unspecified (E7800), as can be seen on Figure 1. A notable variation can be observed when examining the months of November and December in 2020. In these months, the diagnosis Contact with and (suspected) exposure to other viral communicable diseases transitions from the third to the second position, indicating a higher occurrence of COVID-19 in December compared to November. This shift in ranking provides valuable insights into the increased prevalence of this diagnosis during the month of December. Through this analysis, we aim to examine the transformations that have taken place as a result of the pandemic, particularly in terms of the diagnosis of a specific disease, which has undergone notable changes compared to the pre-pandemic period. We highlight several significant changes that have occurred in defining diagnoses, showcasing the variations observed over the course of a year.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

Анализа на техники за точна и безбедна комуникација (ATCSC)

Една од целите на овој проект ќе биде испитување на перформансите на Брзите алгоритми за крипто кодовите базирани на квазигрупи, за пренос на слики низ Гаусов канал и канал со рафални грешки. Ќе бидат анализирани некои техники за детекција на грешки при пренос на податоци. Друга цел на проектот е откривање на нови скриени канали кај DICOM стандардот кој се користи за процесирање, пренесување, складирање и прикажување на податоци за медицински слики (откривање на скриени канали кои се однесуваат на “DICOM Message Service” и “Upper Layer Service”, експериментална евалуација на некој од предложените скриени канали, детекција базирана на ентропија, утврдување на ризиците од криење на податоци во DICOM со користење на новите предложени канали, предлагање на противмерки за скриените канали). Исто така, ќе бидат направена анализа на предизвиците, ефективноста и последиците од несоодветна употреба на полисите за информациска безбедност. Ќе биде разгледана можна имплементација на HOTP и TOTP автентикациските алгоритми и нивните предности и недостатоци. Ќе бидат анализирани алгоритми за криптоанализа во BlockChain технологија