Preetham Kumar

• Dr.
• Professor at Manipal Academy of Higher Education

Fundus Fluorescein Angiography (FFA) is an important invasive diagnostic tool employed in ophthalmology for the assessment of retinal and choroidal blood flow, components situated at the rear of the eye. Identifying lesions within FFA images, indicative of anomalies in the retina and choroid visualized through the injection of a fluorescein dye, is...

Data analytics is an integral part of strategic decision making in various fields but not limited to business, education, and healthcare systems. Existing research works focus on the discovery of itemsets with rare antecedents and consequent or frequent antecedents and consequent. Analysis of association among itemsets with rare antecedents and fre...

A major setback in Deep Learning (DL) is that a huge amount of data is essential to render the trained model more generalizable. Constructing a higher-order model based on insufficient data has a detrimental effect on testing performance. Transfer Learning (TL) involves less training data than conventional DL approaches and offers superior decision...

Diabetic Macular Edema (DME) is a severe ocular complication commonly found in patients with diabetes. The condition can precipitate a significant drop in VA and, in extreme cases, may result in irreversible vision loss. Optical Coherence Tomography (OCT), a technique that yields high-resolution retinal images, is often employed by clinicians to as...

Diabetic Macular Edema (DME) represents a significant visual impairment among individuals with diabetes, leading to a dramatic reduction in visual acuity and potentially resulting in irreversible vision loss. Optical Coherence Tomography (OCT), a technique that produces high-resolution retinal images, plays a vital role in the clinical assessment o...

Glaucoma is an optic neuropathy, which leads to vision loss and is irreversible due to damage in the optic nerve head mainly caused by increased intra-ocular pressure. Retinal fundus photography facilitates ophthalmologist in detection of glaucoma but is subjective to human intervention and is time-consuming. Computational methods such as image pro...

Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is characterized by a buildup of extracellular fluid inside the macula through hyperpermeable vessels. The presence of DME can be spotted at any level of DR with varying degrees of severity us...

Time and space utilization for discovering interesting patterns from a database plays an important role in analyzing information for major sectors like education, medicine, and e-business. Association rule mining (ARM) technique is used to discover associations among the patterns from large volumes of data. In most ARM algorithms, rare and frequent...

The world is significantly affected by infectious coronavirus disease (covid-19). Timely prognosis and treatment are important to control the spread of this infection. Unreliable screening systems and limited number of clinical facilities are the major hurdles in controlling the spread of covid-19. Nowadays, many automated detection systems based o...

Glaucoma is one of the leading cause of blindness for over 60 million people around the world. Since a cure for glaucoma doesn’t yet exist, early screening and diagnosis become critical for the prevention of the disease. Optic disc and optic cup evaluation are one of the preeminent steps for glaucoma diagnosis. A novel approach is developed in this...

Itemset mining discovers interesting patterns in the dataset. The itemset may be frequent or it can be rare based on its occurrence in the database. It has been observed that most of the algorithms are designed for mining frequent itemsets. However, discovery of rare itemsets is equally important since they play a major role in making decisions in...

Glaucoma is a progressive optic neuropathy, which damages the optic nerve head and causes irreversible visual field loss. It is considered as one of the major cause of blindness. Clinical diagnosis of glaucoma involves fundus photography for examining the changes occurring due to glaucoma. Fundus images are capable of being processed by computation...

Automated segmentation of optic disc in fundus images plays a vital role in computer aided diagnosis (CAD) of eye pathologies. In this paper, a novel method is proposed which detects and excludes the blood vessel for accurate optic disc segmentation. This is achieved in two steps. First, an effective blood vessel detection and exclusion algorithm i...

Blood is composed of white blood cells, red blood cells, and platelets. Segmentation of the blood smear cells and extraction of features of the cells is essential in the field of medicine. Acute lymphoblastic leukemia is a form of blood cancer caused due to the abnormal increase in the production of immature white blood cells in the bone marrow. It...

Cervical Cancer arises in the Cervix. Cancer progresses slowly from normal stage to pre-cancerous stage, and hence it provides an opportunity to diagnose it and prevent it. Visual inspection of the pap smear is tedious and time-consuming. Commercial systems for automated analysis are costly which makes it unaffordable for most hospitals. The primar...

Red blood cell count plays a vital role in identifying the overall health of the patient. Hospitals use the hemocytometer to count the blood cells. Conventional method of placing the smear under microscope and counting the cells manually lead to erroneous results, and medical laboratory technicians are put under stress. A computer-aided system will...

Blood cell segmentation and extraction of characteristics of cells plays a vital role in the field of medicine. Blood count is used to analyze the overall health of a person. It can be used to identify diseases like anemia, infection and leukemia. White Blood cells, Red Blood cells and platelets forms the parts of blood. In laboratory, blood cell c...

In this paper, the proposed method reduces CPU computation time by reducing transaction scan. The Concept infrequent count is based on minimum threshold support and 2-way searching to reduce execution time during scanning of transaction is introduced in proposed method. There exist several data mining algorithms for finding association rules but on...

In todays world there is a wide availability of huge amount of data and thus there is a need for turning this data into useful information which is referred to as knowledge. This demand for knowledge discovery process has led to the development of many algorithms used to determine the association rules. One of the major problems faced by these algo...

Every year massive amount of feedback is gathered from students regarding subjects and its respective faculty. The amount of time to analyze this data manually is a very tedious and time consuming. This is where the summarization feature comes into picture. It extracts important information found in every feedback document. Automatic summarization...

Data mining is the practice to search large amount of data to discover data patterns. Data mining uses mathematical algorithms to group the data and evaluate the future events. Association rule is a research area in the field of knowledge discovery. Many data mining researchers had improved upon the quality of association rule for business developm...

The paper highlights a unique and secure way of retrieving data, where user can never identify the path followed by the system to reach the goal. The whole collection of data is represented in Boolean form which is stored in a matrix. This matrix can be used for quick retrieval of data as all the functions and properties of mathematical logic can b...

Association rules play a very vital role in the present day market that especially involves generation of maximal frequent itemsets in an efficient way. The efficiency of association rule is determined by the number of database scans required to generate the frequent itemsets. This in turn is proportional to the time, which will lead to the faste...

Association rules play a very vital role in the present day market that especially involves generation of maximal frequent itemsets in an efficient way. The efficiency of association rule is determined by the number of database scans required to generate the frequent itemsets. This in turn is proportional to the time, which will lead to the faster...

Weighted tree mining has become an important research topic in Data mining. There are several algorithms for mining Frequent Pattern trees. FP growth algorithm using FP tree has been considered for frequent pattern mining because of its enormous performance and development compared to the candidate generation model of Apriori. The purpose of our wo...

The abstraction based algorithms read databases in sequential order and then construct abstraction of the database in memory. Given any database with n attributes, it is possible to read the same in n! ways. These different n! ways lead to abstractions of different sizes. In this paper, for a given a set of transactions D, we find the sequence or o...

Mining of association rules for basket databases, has been investigated by, etc. Most of these works focus on mining binary association rules, i.e, most of the association rules mining algorithms to discover frequent itemsets do not consider the quantity in which items have been purchased. This paper discusses an efficient method for discovering a...

Most of the association rules mining algorithms to discover frequent itemsets do not consider the components of transactions such as number of items bought or quantity and its total cost. In a large database it is possible that even if the itemset appears in a very few transactions, it may be purchased in a large quantity for every transaction in w...

Every element of the transaction in a transaction database may contain the components such as item number, quantity, cost of the item bought and some other relevant information of the customer. Most of the association rules mining algorithms to discover frequent itemsets do not consider the components such as quantity, cost etc. In a large database...

For an N-attributed database i.e. database storing the non-binary values of N number of attributes, a great deal of saving in space can be achieved while representing the database on the lines similar to PC-Tree, by determining the sequence of attributes (sorting order) to be considered constructing the tree. In order to avoid the ordinary and high...

The Need to extract the association rules from th e pool of varied data, having gained increased momentum in the field of data mining, necessitates the discovery of methods to process multi-dimension al data, and find the qualitative or quantitative associatio n rules from it by considering all the relevant fie lds in an efficient manner In this pa...