The aim of this study was an investigation whether the examined subjects can be classified as normal, myopathic or neuropathic, based on 4-channel surface electromyographic (SEMG) recordings of the biceps brachii muscle recorded at isometric voluntary contractions. Five different force levels were used: 10, 30, 50, 70 and 100 % of maximum voluntary contraction (MVC), with each recording lasting...

The nature of clinical data makes it difficult to quickly select, tune and apply machine learning algorithms to clinical prognosis. As a result, a lot of time is spent searching for the most appropriate machine learning algorithms applicable in clinical prognosis that contains either binary-valued or multi-valued attributes. The study set out to identify and evaluate the performance of machine ...

The paper presents aspects regarding genetic algorithms, their use in data mining and especially about their use in the discovery of classification rules. A synthetic presentation of the fitness functions of the genetic algorithms used for mining the classification rules is performed. A genetic algorithm with a new fitness function for mining the classification rules is suggested. The proposed ...

Thetaskofextractingtheusedfeaturevectorinminingtasks(classification,clustering...etc.)is consideredthemostimportanttaskforenhancingthetextprocessingcapabilities.Thispaperproposes anovelapproachtobeusedinbuildingthefeaturevectorusedinwebtextdocumentclassification process;addingsemanticsinthegeneratedfeaturevector.Thisapproachisbasedonuti...

Breast cancer has become the primary reason of death in women in developed countries. Breast cancer is the second most common cause of cancer death in women worldwide. The high incidence of breast cancer in women has increased significantly during the last few decades. In this paper we have discussed various data mining approaches that have been utilized for early detection of breast cancer. Br...

In this paper, we develop a heart disease prediction model that can assist medical professionals in predicting heart disease status based on the clinical data of patients. Firstly, we select 14 important clinical features, i.e., age, sex, chest pain type, trestbps, cholesterol, fasting blood sugar, resting ecg, max heart rate, exercise induced angina, old peak, slope, number of vessels colored,...

Numerous data mining techniques have been developed to extract information and identify patterns and predict trends from large data sets. In this study, two classification techniques, the J48 implementation of the C4.5 algorithm and a Naive Bayes classifier are applied to predict lung cancer survivability from an extensive data set with fifteen years of patient records. The purpose of the proje...

The bank conducts an analysis or survey in the credit system to determine whether customer is eligible receive credit. With a case study of Bank BJB debtor data December 2021, classification was carried out by forming model using Naïve Bayes Classifier and Decision Tree J48. Thus it expected minimize occurrence bad loans. are divided into several categories: debtors with good, substandard, doub...