Selected morphotic parameters differentiating ulcerative colitis from Crohn’s disease

This paper presents a method that binds statistical and data mining techniques, which aims to support the decision-making process in selected diseases of the digestive system. Currently, there is no precise diagnosis for ulcerative colitis (UC) and Crohn's disease (CD). Specialist physicians must exclude many other diseases occurring in the colon. The first goal of this study is a retrospective analysis of medical data of patients hospitalised in the Department of Gastroenterology and Internal Diseases, Bialystok, and finding the symptoms differentiating the two analysed diseases. The second goal is to build a system that clearly points to one of the two diseases UC or CD, which shortens the time of diagnosis and facilitates the future treatment of patients. The work focuses on building a model that can be the basis for the construction of action rules, which are one of the basic elements in the medical recommendation system. Generated action rules indicated differentiating factors, such as mean corpuscular volume, platelets (PLTs), neutrophils, monocytes, eosinophils, basophils, alanine aminotransferase (ALAT), creatinine, sodium and potassium. Other important parameters were smoking and blood in stool

Comparative Evaluation of the Different Data Mining Techniques Used for the Medical Database

Data mining is the upcoming research area to solve various problems. Classification and finding association are two main steps in the field of data mining. In this paper, we use three classification algorithms: J48 (an open source Java implementation of C4.5 algorithm), Multilayer Perceptron - MLP (a modification of the standard linear perceptron) and Naïve Bayes (based on Bayes rule and a set of conditional independence assumptions) of the Weka interface. These classifiers have been used to choose the best algorithm based on the conditions of the voice disorders database. To find association rules over transactional medical database first we use apriori algorithm for frequent item set mining. These two initial steps of analysis will help to create the medical knowledgebase. The ultimate goal is to build a model, which can improve the way to read and interpret the existing data in medical database and future data as well

Decision-Making Process in Colon Disease and Crohn’s Disease Treatment

The article presents the process of building a logistic regression model, which aims to support the decision-making process in medicine. Currently, there is no precise diagnosis for ulcerative colitis (UC) and Crohn's disease (CD). Specialist physicians must exclude many other diseases occurring in the colon. The first goal of this study is a retrospective analysis of medical data of patients hospitalized in the Department of Gastroenterology and Internal Diseases and finding the symptoms differentiating the two analyzed diseases. The second goal is to build a system that clearly points to UC or CD, which shortens the time of diagnosis and facilitates the treatment of patients. The work focuses on building a model that can be the basis for the construction of classifiers, which are one of the basic elements in the medical recommendation system. The developed logistic regression model will define the probability of the disease and will indicate the statistically significant changes that affect the onset of the disease. The value of probability will be one of the main reasons for the decision

Smart Model to Distinguish Crohn’s Disease from Ulcerative Colitis

Inflammatory bowel diseases (IBD) is a term referring to chronic and recurrent gastrointestinal disease. It includes Crohn’s disease (CD) and ulcerative colitis (UC). It is undeniable that presenting features may be unclear and do not enable differentiation between disease types. Therefore, additional information, obtained during the analysis, can definitely provide a potential way to differentiate between UC and CD. For that reason, finding the optimal logistic model for further analysis of collected medical data, is a main factor determining the further precisely defined decision class for each examined patient. In our study, 152 patients with CD or UC were included. The collected data concerned not only biochemical parameters of blood but also very subjective information, such as data from interviews. The built-in logistics model with very high precision was able to assign patients to the appropriate group (sensitivity = 0.84, specificity = 0.74, AUC = 0.93). This model indicates factors differentiating between CD and UC and indicated odds ratios calculated for significantly different variables in these two groups. All obtained parameters of the model were checked for statistically significant. The constructed model was able to be distinguish between ulcerative colitis and Crohn’s disease

Contrast-Enhanced Ultrasound in the Differentiation between the Most Common Benign Parotid Gland Tumors: A Systematic Review and Meta-Analysis

Recently, contrast-enhanced ultrasound (CEUS) has become a promising tool in distinguishing benign from malignant parotid gland tumors. However, its usefulness in differentiating various benign parotid tumors has not been determined so far. This study aimed to systematically review the literature to determine the utility of CEUS in the preoperative differentiation between pleomorphic adenomas (PAs) and Warthin’s tumors (WTs) of the parotid gland. PubMed, Embase, and Cochrane were searched for English-language articles published until 21 July 2022. Fifteen studies were included. On CEUS examination, a significantly greater percentage of PAs displayed heterogeneous enhancement texture compared to WTs. Contrarily, the enhanced lesion size, the enhancement margin, and the presence of the enhancement rim did not differ significantly between the entities. Significantly longer normalized mean transit time (nMTT) and time to peak (TTP) were observed in PAs. Contrarily, the mean values of area under the curve (AUC) and time from peak to one half (TPH) were significantly higher for WTs. Due to the considerable overlap among the qualitative CEUS characteristics of PAs and WTs, the reproducible, investigator-independent quantitative CEUS measurements have a greater potential to distinguish PAs from WTs, which might influence the selection of an appropriate management strategy

External validation of the Ruptured Arteriovenous Malformation Grading Scale (RAGS) in a multicenter adult cohort

While Ruptured Arteriovenous Malformation Grading Scale (RAGS) has recently been validated in children, the literature lacks validation on adults exclusively. Therefore, we aimed to determine the validity of RAGS on the external multicenter adult cohort and compare its accuracy with other scales