Breast cancer is one of the most common types of cancer among women worldwide, therefore an early and precise process of diagnostics plays an important role in improving the prognosis and outcome of treatment. The application of artificial intelligence (AI) allows faster and more precise analysis of medical imaging, which contributes to the early detection of tumors and lowers the number of false-negative results. This review article analyzed 60 scientific papers and using the most recent findings about this topic, searched for AI implementation in breast cancer research and how AI may improve overall survival outcomes for breast cancer patients.

Introduction: Breast cancer (BC) is a malignant disease that predominantly affects women, with known genetic components such as mutations in tumor suppressor genes BRCA1 and BRCA2. Other risk factors include unhealthy lifestyles, lack of physical activity, and consumption of alcohol and cigarettes. Aging also plays a role in BC development, with hormonal influences such as estrogen and progesterone promoting cancer growth. Material and Methods: Research was conducted using data collection tools for risk factors and tumor markers from primary healthcare unit records. The sample comprised 200 women, divided into two groups based on BC diagnosis, with complete medical documentation. Male BC cases were excluded. Results: Statistical significance was found between genetic components, family history, aging, obesity, alcohol and cigarette consumption, longer hormone exposure, and female BC development using the Chi-Square test, confirmed by Fisher's Exact test. Tumor markers CA 15-3, CEA, CA 19-9, and CA 125 were useful for BC screening and metastasis detection, as determined by the One Sample T-test. In Sarajevo Canton, invasive ductal BC was the most common type among women, while lobular carcinoma in situ was the least common. Conclusion: Correlations between risk factors, including aging, unhealthy lifestyles, and hormone exposure, and increased BC risk were confirmed. Tumor markers CA 15-3, CEA, CA 19-9, and CA 125 were effective in diagnosis, screening, and metastasis detection in females, with sensitivity for regression detection at 81.8% and specificity at 100%.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has caused a worldwide emergency. The disease is characterized primarily by symptoms of the respiratory system, but also by systemic inflammation. Since the onset of the disease, there has been a need for biomarkers to predict the severity of the clinical picture and the outcome of the disease. The aim of this study is to evaluate systemic inflammatory markers for predicting severity of COVID-19. Methods: The study was conducted at the Sarajevo Canton Health Center on a total of 170 adults suffering from COVID-19. 70 subjects had mild clinical picture, while the control group consisted of 100 subjects with moderate clinical picture. The results of complete and differential blood counts, C-reactive protein (CRP), and systemic inflammatory indexes (SII) (neutrophil/lymphocyte ratio [NLR], derived NLR [dNLR], platelet/lymphocyte ratio [PLR], and SII) were used to compare the groups. IBM SPSS Ver. 23 was used for statistical analysis and data processing. Results: The proportion of male patients in the group with a milder clinical picture was higher than the proportion of male patients with a moderate clinical picture, p = 0.016. The values of leukocytes and neutrophils were higher in patients with a moderate clinical picture (p = 0.006 and p < 0.001, respectively). The values of all inflammatory indexes (NLR, dNLR, PLR and SII) were higher in patients with a moderate clinical picture of COVID-19 than in patients with a mild clinical picture (p < 0.001 for NLR, dNLR, and SII; p = 0.023 for PLR). In the research, patient age showed no correlation and CRP showed no correlation with SII. Conclusion: SII show higher values in patients with a moderate compared with a mild clinical picture of COVID-19. These parameters can be cost-effective and useful indicators in patient classification, diagnosis, and probably in monitoring patients with COVID-19.

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Background: Psoriasis as an immune-mediated inflammatory skin disease. The basis of the pathogenesis of psoriasis is the dysregulation of immune cell function in genetically predisposed individuals. The characteristic dysfunction of the immune system in patients with psoriasis is manifested as a variation in the cellular phenotypic profile in accordance with the disease status. Objective: The aim of this study was to evaluate the immunophenotypic profile of lymphocytes obtained by flow cytometry as an auxiliary diagnostic tool in the objectivization of the PASI score. Methods: The study group included 40 patients with psoriasis, hospitalized and treated at Dermatology Clinic of Clinical center University of Sarajevo and 30 healthy individuals as controls. After venepunction, the blood samples for determining the immune profile were prepared following standard laboratory procedures using conjugated monoclonal antibodies and BD FACSCanto II flow cytometer. T-lymphocytes (CD3, CD4, CD8), B lymphocytes (CD19), Natural killer cells (NK), and activatet T-cells (CD3HLA) were determined for all patients. Based on the PASI score, the severity and area of the disease was assessed for all psoriasis patients by dermatology specialist. Results: Our data shows no significant difference in any of the lymphocyte subpopulations between psoriasis patients and healthy controls, except CD3HLA. CD3HLA has higher values in patients with psoriasis, p=0.015. Of all the parameters, only NK cells were significantly correlated to the PASI score (rho -0.279; p=0.048). ROC curve analysis revealed a statistically significant difference for the proportion of CD3 lymphocytes (AUC 0.799; p=0.004), CD8 lymphocytes (AUC 0.733; p= 0.023), NK cells (AUC 0.722; p=0.008) and CD3HLA activated T lymphocytes (AUC 0.347; p=0.034). Conclusion: Profile of major lymphocyte subsets in patients with psoriasis is similar to that of healthy controls. The values of CD3, CD8, NK, CD3HLA were defined as biomarkers capable of distinguishing psoriasis according to the severity of the disease. Immunophenotyping of peripheral blood lymphocytes can play an important role as an auxiliary diagnostic method in differentiating the clinical stages of psoriasis and objectifying the PASI score.

Introduction: COVID-19 is an infectious disease caused by the severe acute respiratory syndrom coronavirus 2 and causes a series of respiratory symptoms. Considering the appearance and development of symptoms, the course of COVID-19 can go from mild to severe. Depending on the course of COVID-19, the laboratory parameters change a lot, trying to defend the organism against the foreign pathogen and all the changes it causes. Therefore, the aim of this study is to observe the differences between biochemical, hematological and coagulation parameters depending on the disease stage of COVID-19 patients. Material and methods: We conducted cross-sectional study which included 160 COVID-19 patients from Sarajevo, Bosnia and Herzegovina. Biochemical, hematological and coagulation analyzes were performed. Results: COVID-19 patients with a severe clinical course have higher average values of fibrinogen (6.53±4.47,p<0.001), D-dimer (6.89±7.81, p<0.001), APTT (32.05±5.96, p=0.002), eosinophil (0.66±0.09, p=0.002) and CRP (93.42±75.86, p= 0.023), and lower values of lymphocytes (1.04±0.98, p<0.001), monocytes (0.45±0.3, p<0.001), compared to COVID-19 patients with a mild clinical course. COVID-19 patients with a severe clinical course had higher average values of neutrophils (10.12±5.80, p=0.002) and lower values of reactive lymphocytes (0.02±0.03, p<0.001) compared to COVID-19 patients with a mild clinical course. Conclusion: Biochemical, hematological and coagulation parameters can be a sensitive and specific biomarker for distinction of mild and severe COVID-19.

Introduction: Laboratory personnel (LP) represent a high-risk group of healthcare workers for whom the primary laboratory environment and specific work activities are a major source of potential exposure to health hazards. This study aimed to evaluate the developed matrix and assess risk based on self-assessment. Methods: This multicenter, qualitative, and cross-sectional study was conducted on LP employed in biomedical laboratories. The respondents were divided into groups according to their territorial affiliation. The data collection tool used was a six-area questionnaire distributed online through a network of professional associations. For the risk assessment, a matrix was developed with scores ranging from 0 to 650, dividing the risk level into four categories. Descriptive and inferential statistical methods were used for the statistical analysis. Results: The developed model combined the classification of risk and risk factors with a certainty of p < 0.001. The regression analysis showed that working conditions had the greatest influence on overall risk, followed by physical, biological, and physical hazards. Of the 640 respondents, the medium risk category was the highest in European Union (EU) countries (81.2%). Comparing the values in the high-risk category between the Bosnians and Herzegovinians (BiH) group and the Republic of Serbia, Republic of Northern Macedonia, and Montenegro (SCM) group with the EU group, a doubling (16.6%: 36.7%) and tripling (16.6%: 52.1%) of the proportion was found, respectively (p < 0.001). Overall, 1.7% of the LPs from BiH fell into the high-risk category. Conclusions: The designed matrix provides a reliable basis for identifying risk predictors in the study population and can serve as a useful tool for conducting risk assessments in biomedical laboratories. The results of the risk assessment indicate significant differences between the studied groups and highlight the need for increased control of BiH workplaces through new regulatory requirements.

INTRODUCTION: Inflammatory bowel disease (IBD) comprising ulcerative colitis (UC) and Crohn disease (CD), affects >1 million individuals in the United States and 2.5 million inEurope. IBD is an immune-mediated chronic condition for which currently no definitive cure is available. The current study utilizes apositive psychology framework to understand the role of stress in IBD, seeks a proof ofconcept that stress resilience could be a protective factor in patients with IBD. Resilienceis defined as the inherent and modifiable capacity of an individual to cope or recover from adversity. OBJECTIVE: On the basis of previous knowledge, we want explain and bring closer the understanding of the resilience of patients with inflammatory bowel diseases. METHODS: The PubMed database, and the Google scholar database were searched. The search was performed using keywords. This paper includes research dealing with resilience in patients with inflammatory bowel diseases within the last ten years. RESULTS: Although IBD imposes a mental and physical toll on individuals, someindividuals do report feeling stronger due to having IBD. Most studies included in this review investigated psychological resilience and trait resilience that promoted the ability to bounce back from IBD-related adversity. Conversely, higher levels of resilience were found to predict better quality of life among IBD patients. Higher levels of resilience predicted higher levels of adaptation to the ostomy; notably, perseverance— defined as a trait of resilience was the most reliable predictor. Resilience was not significantly affected by clinical characteristics in UC patients. CONCLUSION: Many unmet needs still exist in the IBD research agenda, including a better understanding of its physiopathology, reduction of diagnostic delays, discovery of more effective and safer drugs, optimisation of existing therapies, improving patients’ adherence to the treatment plan, improving patient’s quality of life, management of extraintestinal manifestations, and prevention of complications. A multidimensional approach is necessary for delivering high-quality healthcare for IBD patients.

INTRODUCTION Anxiety is a state of feeling helpless and insecure, a state of anticipation and concern that something bad will happen. Fear of pain and the unknown, as well as fear of screening results can increase anxiety. Severe anxiety during magnetic resonance imaging (MRI)can cause patient's movement, leading to poorer imaging and reduction in the quality of the diagnostic test. To determine the anxiety of patients before and after magnetic resonance imaging and to investigate the relationship between the tested anxiety and the socio-demographic characteristics of the patients. METHODS The study was conducted at the Department of Radiology of the University Clinical Hospital Mostar in the period from February 1st 2020 to March 31st 2020. The study included 100 subjects who were prescribed an MRI screening at the time of the study. A socio-demographic questionnaire specifically designed for this study was used to obtain data on subjects such as gender, age, place of residence, smoking, drinking alcohol, economic status, religiosity. The Anxiety Questionnaire as a State-Trait Anxiety Inventory (STAI) was used to examine anxiety. RESULTS A statistically significantly higher degree of anxiety was determined after MRI screening (p<0.001). Male subjects achieved a statistically significantly higher degree of anxiety before (p=0.019) and after (p=0.034) MRI screening. There were no statistically significant correlations between the age of the subjects and the results achieved on the anxiety tests before and after the MRI screening. CONCLUSION Subjects who were prescribed an MRI screening have a statistically significantly higher degree of anxiety after the screening. Male subjects had a statistically significantly higher degree of anxiety on MRI screening.