Routine Identification of Melanoma Disease using Global and Local Features

This paper focuses on the finding, segmentation, categorization and removal of skin lesion as a literature survey. Melanoma is a category of cancer that develop from the pigment-network cells renowned as melanocytes. Melanomas usually develop in the skin other than may arise in the maw, backbone or ogle. This paper addresses two different systems for finding of fur evil in dermoscopy images. The first system uses global features and the second system uses local methods and the classifier. Therefore, melanoma is simply to identify with help of global features and local methods. Keywords: Melanocytes, classifiers, finding, segmentation, categorization, removal, fur lesions

Detection of Melanoma Disease using Image Processing

The aim of fur lesion categorization is applicable to both MSL’s and NMSL’s has involved investigate area as cruelty of the infection in the early stage is low. The routine categorization of MSL’s has been projected in this work. To begin with the imagery are segmented and its overall and limited description are extract using speeded up robust feature methods which are additional occupied to categorize fur lesion. Then, a set of feature from starting the speeded up robust features using the unverified categorization using genetic method to present binary categorization as tumour or benevolent. The intensity of the NMSL affect pathway can be detect and analyzed using color, SR, texture. Ex-perimental result demonstrate that the projected scheme out-perform other than categorization method in conditions of sen-sitivity and spe-cificity . Keywords: Color, Sub region, texture, RGB colors, Fitness and population methods, Gaussian filter, Sobel Edge Detection, Gray level co occurrence matrix

COVID-19 and Mental Health: A Cross-Sectional Study on Mental Health Impact Of COVID-19 Among People In Kerala

The global pandemic COVID-19 has raised an enormous threat to the world’s health care services, economy, socio-political bodies, and infrastructure. This pandemic has negatively affected both physical and mental health. Mental well- being is more than the existence or absence of mental illness. It is an intersection between emotional, psychological, social, and physical well-being. Many persons have experienced significant mental health problems this year. Public health interventions related to COVID-19, including quarantines and lock-downs, can have a detrimental effect on people’s mental health status through environmental change, disruption of services, self, social isolation, financial uncertainty, and work loss enhanced stress. The purpose of the study was to investigate the gender differences of mental health (perceived stress, anxiety, and depression) and explored associated factors during the COVID-19 epidemic among peoples living in Alappuzha, Pathanamthitta, and Kollam district

Strong Domination Index in Fuzzy Graphs

Topological indices play a vital role in the area of graph theory and fuzzy graph (FG) theory. It has wide applications in the areas such as chemical graph theory, mathematical chemistry, etc. Topological indices produce a numerical parameter associated with a graph. Numerous topological indices are studied due to its applications in various fields. In this article a novel idea of domination index in a FG is defined using weight of strong edges. The strong domination degree (SDD) of a vertex u is defined using the weight of minimal strong dominating set (MSDS) containing u. Idea of upper strong domination number, strong irredundance number, strong upper irredundance number, strong independent domination number, and strong independence number are explained and illustrated subsequently. Strong domination index (SDI) of a FG is defined using the SDD of each vertex. The concept is applied on various FGs like complete FG, complete bipartite and r-partite FG, fuzzy tree, fuzzy cycle and fuzzy stars. Inequalities involving the SDD and SDI are obtained. The union and join of FG is also considered in the study. Applications for SDD of a vertex is provided in later sections. An algorithm to obtain a MSDS containing a particular vertex is also discussed in the article

CD4 count evaluation in HIV-TB co infection before and after anti-tubercular treatment

Background:The global impact of Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection is one of the major public health challenge. India has a very high burden of TB according to the WHO. A decrease in CD4 counts in HIV-TB co-infection leads to an increase in morbidity and mortality.Methods:Information regarding the duration of HIV, type of TB, CD4 counts before and after ATT and any associated Opportunistic Infections (OIs) were collected from the records of 100 patients with HIV-TB co-infection who attended ART centre for a period of one year. The collected data was statistically analyzed.Results: In the study group, 35 had Pulmonary Tuberculosis (PTB) and 65 had Extra Pulmonary Tuberculosis (EPTB), 40 had OIs. Mean CD4 count prior to ATT in PTB was 197 (7-940), EPTB 192 (13-683) and with OIs 129 (7-288). After completion in PTB was 300, EPTB 302 and 252 in OIs. Least CD4 count of 121 was observed in patients above 50yrs and after completion it was 133. Incidence of both EPTB and PTB was higher in males 66.2% and 62.9%, and in the age group of 31-50 yrs 50.8% and 60% (Cell counts expressed in cells/µl.).Conclusion:In our study, we found that there was significant recovery of CD4 cells following ATT. Difference in CD4 counts among patients with PTB and EPTB was not significant. There was remarkable reduction of CD4 counts in patients who had other OIs and the recovery after ATT was also marginal.

An Empirical Model of Supervised Learning for Electronic Health Records

Examining the health records is an interesting research issue in the field of medical knowledge and data engineering. Electronic health records are basic sources which maintains the patient health information that contains vitals, demographics and encounter or episode information. We propose an empirical model of classification approach for analyzing the test samples with training samples of electronic health records. We use improved supervised learning model to classify the health records. Our proposed model gives efficient results than traditional approaches

Aerobic bacterial profile and their antimicrobial sensitivity pattern in patients of otitis media with ear discharge

Background: The average prevalence of Chronic suppurative otitis media (CSOM) in India is 5.2%. It is more prevalent due to various predisposing factors such as malnutrition, overcrowding, poor hygiene, inadequate health care, and recurrent upper respiratory tract infection. In recent years, there is increased preponderance of multi drug resistant organisms due to the irrational use of antibiotics, making treatment of CSOM more difficult.Methods: Samples from 100 subjects of uncomplicated CSOM who presented to the Oto-Rhino-Laryngology outpatient department of our hospital were collected. Aerobic bacterial profile and its Antimicrobial susceptibility were studied by conventional methods. Results were compiled and evaluated by descriptive statistics and inferential statistics.Results: Pseudomonas aeruginosa (50.7%) and Staphylococcus aureus (19.04%) were the predominant isolates in our study. Aminoglycosides and Fluoroquinolones were found to be effective first line drugs, followed by Carbapenems.Conclusions: These antibiotics can be used to prevent the life-long complications of CSOM. Timely culture and sensitivity helps in the management of these cases.

Domination Index in Graphs

The concepts of domination and topological index hold great significance within the realm of graph theory. Therefore, it is pertinent to merge these concepts to derive the domination index of a graph. A novel concept of the domination index is introduced, which utilizes the domination degree of a vertex. The domination degree of a vertex a is defined as the minimum cardinality of a minimal dominating set that includes a. The idea of domination degree and domination index is conducted of graphs like complete graphs, complete bipartite, r partite graphs, cycles, wheels, paths, book graphs, windmill graphs, Kragujevac trees. The study is extended to operation in graphs. Inequalities involving domination degree and already established graph parameters are discussed. An application of domination degree is discussed in facility allocation in a city. Algorithm to find a MDS containing a particular vertex is also discussed in the study