Association rule mining is a procedure which aims to observe frequently occurring patterns, correlations, or associations from datasets found in various kinds of databases such as relational databases, transactional databases, and other forms of repositories. The Association rule furthermore looks for interesting associations among the variables of the dataset. (Abhinav Rai, 2022) Then, depending on the following two parameters, the important relationships are observed: Support: Support indicates how frequently the if/then relationship appears in the database. Confidence: Confidence tells about the number of times these relationships have been found to be true. (Abhinav Rai, 2022) Association rules for medical purposes can help doctors diagnose and treat patients. Diagnosis is a difficult procedure with many potential errors that might lead to incorrect findings. We may use association rule mining to determine the probability of diseases based on multiple parameters and indicators. This method may also be developed using learning approaches by adding additional indicators and identifying connections between the new indicators and the related illnesses. In this work, we will try to find the relationship between several indicators including the Occurrence of nausea, Lumbar pain, Urine pushing, Micturition pains and Burning of the urethra with two diseases named Inflammation of urinary bladder and Nephritis of renal pelvis origin. The result helps doctors to make better and more accurate decisions.
The main goal of this data set is to construct the expert system's algorithm, which will provide the probable diagnosis of two urinary system diseases. It will be used to evaluate acute urinary bladder inflammation and acute nephritis. Consider the definitions of both diseases provided by doctors for a better grasp of the issue. Acute urinary bladder inflammation is determined by the rapid appearance of pains in the abdomen region and urination in the form of frequent pee pushing, micturition pains, and, in some cases, a lack of urine keeping. The body's temperature is rising, although it rarely rises over 38 degrees Celsius. The urine is dark and occasionally red. Symptoms normally disappear after a few days of good treatment. But, there is a strong desire to return. We should expect the sickness to become chronic in people who have acute urinary bladder inflammation. Acute nephritis of the renal pelvis affects females far more frequently than males. It starts with a high fever that reaches and occasionally exceeds 40 degrees Celsius. Shivers and one- or both-side lumbar pains, that may be severe, accompany the fever. Acute inflammation signs of the urinary bladder arise often. There is typically nausea and vomiting, as well as pains that extend throughout the abdomen.“Acute Inflammations Data Set” is selected from UCI Machine Learning Repository.
There are 120 rows in the Acute Inflammations Data Set includes 6 attributes and two columns which are about Inflammation of the urinary bladder and Nephritis of renal pelvis origin. Data preprocessing is an important step before any data mining operation. So, let’s explain loaded packages and reading the dataset file as a data frame.