ASSOCIATION BETWEEN ALPHA-FETOPROTEIN AND OTHER SEROLOGICAL MARKERS IN PATIENTS WITH HEPATOCELLULAR CARCINOMA: ONE CENTER'S EXPERIENCE

Purpose: In this study, we analyzed biochemical parameters in the serum of patients with a diagnosis of hepatocellular carcinoma (HCC) C and B viral aetiology. Material/Methods: All patients (31 males and 20 females) with a diagnosis of HCC that were treated at the Clinical Centre of the University of Sarajevo were included in this retrospective-prospective study. Serum alpha-fetoprotein was analyzed as a tumour marker, and hepatitis markers included HBs Ag, anti-HBs, anti-HBc, anti-HCV and anti-HB. Spearman test and Kolmogorov-Smirnov test were used for correlation and normality analysis, respectively. Results: The largest number of patients (68.62%) had cirrhosis of C viral aetiology that developed in cancer. Hepatocellular carcinoma was diagnosed more in men than in women (60.78%). The most patients were middle-aged (41-64 years). HCC was present in the right liver lobe at 82.85% HCV and 87.5% HBV patients. Only 6.25% of HBV patients were both liver lobes affected. All biochemical parameters had very high values, especially AFP and γGT. Significant differences for AST and ALT were found between men and women. Serum bilirubin levels (total, direct and indirect) and AP are higher in men than in women. Hepatitis markers had high values, and the incidence of HBs Ag (78%) and anti-HBc (78.72%) was established. Conclusions: A positive correlation was established between AFP and other parameters, while a significant difference between AFP and γGT (r = 0.372, p = 0.008) was confirmed. In addition to imaging methods for determining liver cirrhosis and hepatocellular carcinoma, high values of AFP and γGT, are a powerful diagnostic marker for these diseases

Convolutional Neural Networks for Object Classification

Ovaj diplomski rad bavi se konvolucijskim neuronskim mrežama za klasifikaciju objekata. U prvom dijelu diplomskog rada obrađen je pojam umjetnih neuronskih mreža, povijest neuronskih mreža, arhitektura neuronskih mreža, vrste aktivacijskih funkcija, proces učenja neuronskih mreža i algoritam propagacije pogreške unatrag. U drugom dijelu diplomskog rada obrađen je pojam konvolucijskih neuronskih mreža, funkcija konvolucije, filteri za procesuiranje slika, arhitektura konvolucijskih neuronskih mreža, algoritam propagacije pogreške unatrag kod konvolucijskih neuronskih mreža kao i nekoliko primjera konvolucijskih neuronskih mreža. U trećem dijelu diplomskog rada prikazana je praktična primjena konvolucijskih neuronskih mreža za klasifikaciju objekata koja se izvodi u nekoliko koraka: analiza podataka HAM 10000, pretprocesiranje podataka za izgradnju modela, izgradnja modela, testiranje modela i prikaz rezultata kao i buduća poboljšanja modela. Cilj rada je detaljno objasniti pojam konvolucijskih neuronskih mreža i primijeniti iste na vrlo važan problem klasifikacije kožnih oboljenja.This graduate thesis deals with convolutional neural networks for object classifiaction problem. Part one of this graduate thesis deals with artificial neural networks, their history, their architecture, activation functions, process of learning and backpropagation algorithm. Part two of this graduate thesis deals with convolutional neural networks, convolution, picture processing filters, architecture of convolutional neural networks, backpropagation algorithm and a few examples of convolutional neural networks. Part three of this graduate thesis deals with convolutional neural networks for object classification in a few steps: analysing HAM 10000 dataset, preprocessing of the data, building model for object classification and analysing results with future plans. The aim of this graduate thesis was to explain everything about convolutional neural networks and use them on very important problem of skin leasions classification

Convolutional Neural Networks for Object Classification

Ovaj diplomski rad bavi se konvolucijskim neuronskim mrežama za klasifikaciju objekata. U prvom dijelu diplomskog rada obrađen je pojam umjetnih neuronskih mreža, povijest neuronskih mreža, arhitektura neuronskih mreža, vrste aktivacijskih funkcija, proces učenja neuronskih mreža i algoritam propagacije pogreške unatrag. U drugom dijelu diplomskog rada obrađen je pojam konvolucijskih neuronskih mreža, funkcija konvolucije, filteri za procesuiranje slika, arhitektura konvolucijskih neuronskih mreža, algoritam propagacije pogreške unatrag kod konvolucijskih neuronskih mreža kao i nekoliko primjera konvolucijskih neuronskih mreža. U trećem dijelu diplomskog rada prikazana je praktična primjena konvolucijskih neuronskih mreža za klasifikaciju objekata koja se izvodi u nekoliko koraka: analiza podataka HAM 10000, pretprocesiranje podataka za izgradnju modela, izgradnja modela, testiranje modela i prikaz rezultata kao i buduća poboljšanja modela. Cilj rada je detaljno objasniti pojam konvolucijskih neuronskih mreža i primijeniti iste na vrlo važan problem klasifikacije kožnih oboljenja.This graduate thesis deals with convolutional neural networks for object classifiaction problem. Part one of this graduate thesis deals with artificial neural networks, their history, their architecture, activation functions, process of learning and backpropagation algorithm. Part two of this graduate thesis deals with convolutional neural networks, convolution, picture processing filters, architecture of convolutional neural networks, backpropagation algorithm and a few examples of convolutional neural networks. Part three of this graduate thesis deals with convolutional neural networks for object classification in a few steps: analysing HAM 10000 dataset, preprocessing of the data, building model for object classification and analysing results with future plans. The aim of this graduate thesis was to explain everything about convolutional neural networks and use them on very important problem of skin leasions classification

DIFFERENTIAL BLOOD COUNT OF TENCH Tinca tinca (Linnaeus, 1758) IN CONDITIONS OF THERMAL STRESS

Defining the physiological feature provides an understanding of functional adaptation of species to its ecological niche as well as the various forms of stress factors. This paper gives an overview of changes in certain forms of leukocytes (WBC differential) under the influence of thermal stress (increased temperature). In our experiment, we used 46 specimens of tench (Tinca tinca) fished in the Jablanica Lake reservoir. Specimens had previously been adapted in specially prepared tanks for 20 days.  The control group of animals (16) was exposed to constant water temperature of 10 0C, while in the treated groups (30), the water temperature was gradually risen to 28 0C and, as such, held for 30 minutes. All specimens were aged 2+ and 3+.It was found that the thermal regime change causes adaptive response of tench specimens by increasing the number of neutrophils and pseudoeosinophils but reduction in the number of lymphocytes. Observed were statistically significant differences in the number of segmented granulocytes, pseudoeosinophils and lymphocytes between the control and the experimental group. However, a significantly higher number of segmented granulocytes and pseudoeosinophils was at the experimental group, while in the control group a number of lymphocytes was significantly higher compared with the experimental group. Neither form of leukocytes showed any significant difference between males and females of the experimental group. It is interesting to note that among individuals from both the control and experimental group, eosinophils and monocytes were rarely noticed, while basophils were not found at all. Key words: thermal stress, tench, Tinca tinca, pseudoeosinophil