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PREDICTION OF CARDIOVASCULAR DISEASE USING MACHINE LEARNING & DEEP LEARNING TECHNIQUES
Get PDFHealthcare is very important aspects of human life. Cardiovascular disease, also known as the coronary artery disease, is one of the many deadly infections that kill people in India and around the world. Accurate predictions can prevent heart disease, but incorrect predictions can be fatal. Therefore, here this paper describes a method for predicting cardiovascular disease that makes use of Machine Learning (ML) and Deep Learning (DL). The K-Nearest Neighbor method (KNN), Naive Bayes (NB), Decision Tree (DT), Support Vector Machine (SVM), XGBoost (Extreme Gradient Boosting), Artificial Neutral Network (ANN), and Convolutional Neutral Network (CNN) are among the classifiers used in this paper. From Public Health Dataset required data is collected and focused on recognizing the best approach for predicting the disease in preliminary phase. This experiment end results show that the use of Artificial Neural Networks can be of much useful in prediction with better accuracy (95.7%) than compared to any other ML approaches
Nanosponge Gel: A novel therapeutic approach for Rheumatoid Arthritis Treatment
Get PDFNanotechnology and nanomedicines being vast research field offers solutions to many unresolved problems of drug delivery and therapeutics and is an expanding branch of science. Among the available nanoparticles based dosage forms, nanosponges (NS) vanquish the lead because it solubilizes poorly water soluble drugs and prolongs the release of drugs. Nanosponges are very tiny, nanoscopic, sponge-like particles, that consists of a number of cavities filled with medications. Nanosponges have gained attention due to its distinctive characteristics to improve medication delivery systems among the several alternatives. Rheumatoid Arthritis is an autoimmune disease and causes inflammation in the affected parts of the body. Nanosponge gel will be potentially useful for the treatment of Rheumatoid Arthritis. It ensures controlled and prolonged drug release and a good stability. The aqueous solubility of nanosponges allows them to be used efficiently for medications having low solubility. Nanosponges can also act as a vehicle for enzymes, proteins, vaccines and antibodies. The targeting of drug delivery systems by nanosponges is available as a topical administration. The porous shape of nanosponges gives a distinct capacity to entrap medicament and side by side provides the desired release rate. On topical administration it penetrates at the site of action and binds to the receptor site and release the drug in a desirable and predictable manner. The ingredients used, methods of preparation, its characterization, applications as drug delivery system in the field of nanotechnology world are presented in this paper
Role of Curcumin in Protection of Chemobrain via Suppression of Oxidative Stress and Inflammatory Mediators in Swiss Mice
Get PDFBackground: Cyclophosphamide (CP) is a cancer chemotherapeutic agent which shows a cognitive impairment i.e. termed as chemobrain or chemofog. Cyclophosphamide induced cognitive impairement (CICI) is mainly due to generation of reactive oxygen species (ROS) at the cellular level. Curcumin is a natural compound present in the Indian diet as turmeric. Traditionally it is used as analgesic and anti-inflammatory agent. Various pharmacological activities are proven such as antioxidant, anti-cancer and antiapoptotic properties.Objective: In the present study, the neuroprotective effect of curcumin against cyclophosphamide induced cognitive impairment was evaluated on neurobehavioral, neuropathological and biochemical alteration in the adult Swiss mice. Additionally the inflammatory mediators as well as neurotransmitter level were estimated.Methods: Animals were equally divided into five groups of 5 rats in each. Cyclophosphamide were injected intraperitoneally to the animals at dose of 50 mg/kg/week i.p. for 7 days and curcumin at a dose of 200 and 400 mg/kg for 21 days. After 21 days, cognitive dysfunction and motor coordination was assessed behaviorally based on pharmacological models such as passive avoidance test and Rota rod test. After behavioral assessment all the animals were sacrificed for anti-oxidant assay and histopathological studies. Inflammatory mediator Il-6 and neurotransmitter dopamine level were also evaluated in brain homogenate.Results: Data showed that CP significantly elevated brain AChE activity in the brain. A decrease in the total antioxidant capacity and a reduction in the CAT, SOD, and GSH activity occurred in the brains of the rats exposed to CP. CP treated rats showed a significant impairment in long-term- memory and motor coordination. These results were supported by histopathological observations of the brain. Results revealed that the administration of curcumin ameliorated behavioral and histopathological changes induced by CP. Inflammatory mediators were also reduced along with the restoration of dopamine level in the animals treated with curcumin.Conclusion: This study suggests that co-administration of curcumin with cyclophosphamide may be a useful adjunct therapeutic approach to overcome cyclophosphamide induced cognitive impairment
GENOMIC INSIGHTS INTO TASAR SILKWORMS: CORRELATION BETWEEN GENETIC VARIABILITY AND SERICIN QUALITY
Get PDFTasar silkworms (Antheraea mylitta) are crucial for the production of tasar silk, valued for its texture and quality. The role of genetic variability in determining the quality of sericin—a silk protein with significant industrial and biomedical applications—remains underexplored. This study delves into the genomic architecture of Tasar silkworm populations, correlating genetic diversity with sericin quality. Using advanced sequencing technologies, we identify key genetic markers associated with superior sericin properties, providing insights for improving sericulture practices
Designing Integrated Health Monitoring Systems Using Sensors, IoT, and Informatics Tools
Get PDFNew digital health technologies have changed and improved the ways healthcare services are given, overseen and handled. In this paper, we describe a method for designing integrated health monitoring systems using sensors, IoT and health informatics tools. Its objective is to make it easier for people to monitor their health, find diseases early on and receive timely help, mainly for chronic diseases and care of the elderly. We show how these technologies are structured, built and linked and we assess the outcomes of using them in simulation and deployment tests. Results from our research indicate that these platforms offer improved accuracy of data, more active patient involvement and higher healthcare efficiency. With an integrated system, healthcare can provide instant, customized and remote support to patients
Effect of Home Exercise Program in Chronic Non-specific Low Back Pain
Get PDFHome Exercise Programme (HEP) is an alternative to supervised exercise therapy for patients with Chronic Non-Specific Low Back Pain (CNLBP). Complexity and burden of exercises were found to be important barriers related to adherence to HEP, affecting its effectiveness. This pilot study was conducted with 7 CNLBP patients to determine the safety, feasibility, adherence and effectiveness of a simple and graded HEP. The HEP consists of 6 exercises a day, for 5 days a week, for 6 weeks. The outcome measure includes semi-structured questionnaires for assessing feasibility, safety and adherence, Pain intensity, Functional abilities and Quality of Life, was taken at baseline, end of III and VI weeks. Statistical analysis was done by Kruskal Wallis ANOVA. No adverse events were reported and found feasible with 98.41% adherence. Significant improvement was observed in all the outcome measures with p < 0.05. This HEP is a safe, feasible and effective intervention for CNLBP
Lip Morphology Changes After First Premolar Extractions in Patients With Bimaxillary Protrusion in Durg Population: A Pilot Study
Get PDFAim: To determine lip morphology changes after first premolar extractions in patients with bimaxillary protrusion as ratios of hard and soft tissue changes.Materials and Methods: The sample consisted of pretreatment and posttreatment lateral cephalograms of 20 subjects with Class I bimaxillary protrusion who had undergone orthodontic treatment with four first premolars extraction and retraction of upper and lower incisors. Pre and post treatment lateral cephalograms were traced and superimposed by using SN 7˚ plane. Fourteen linear measurements were made. Statistical analysis was performed to analyse the co relation between the hard and soft tissue change by Pearson’s correlation.Results: Significant changes after treatment were found both in dental and lip analysis. The co-relation of hard tissue to soft tissue were derived.Conclusion: statistical analysis revealed that a 1 mm retraction of the incisor cervical point would produce a 0.5 mm retraction of lip. The predictability of this study may be helpful for the clinician in predicting the amount of change in profile of the patient post treatment, thus aiding in planning the treatment
Chemical Characterization of Extracted Ginger Oil Using GCMS
Get PDFAromatic plants are the species whose leaves, flowers, roots or other parts produce and release pleasant smells. Essential oils are plant extracts which are highly concentrated and are obtained from different parts of plants.Steam Distillation method is used to extract the essential oil of Ginger due to its quicker extraction time ,and simplicity of use. Mainly those compounds are separated from this method which are highly sensitive to the temperature. And component are observed after the analysis of GCMS(Gas Chromatography and Mass Spectrometry). After studying we found the component present in ginger are of mainly phenolic and tarpenoid compound. Eugenol is one of the compound which is found as phenolic and Endo Borneol as tarpenoid compound .While having the analysis we found 10 compounds are observed as major in which Eugenol having a percentage of 78.81
A COMPREHENSIVE REVIEW WITH EMPHASIS ON HISTOPATHOLOGICAL EFFECTS
Get PDFBiopesticides offer a sustainable and eco-friendly alternative to conventional chemical pesticides, with the potential to reduce resistance in insect populations. As environmental concerns and pesticide resistance rise, there is growing scientific and industrial interest in the discovery and development of novel bioinsecticides. These biocontrol agents are being increasingly integrated, rotated, or combined within pest management programs as part of ecologically sound practices. Current market trends indicate a 15% annual growth in the biopesticide sector, reflecting the global shift toward environmentally conscious agricultural solutions. This trajectory aligns with the principles of Integrated Pest Management (IPM), promoting reduced chemical dependency. Recent research has expanded the use of microbial agents, particularly novel bacterial species, as effective alternatives to synthetic insecticides. Histopathological studies play a critical role in understanding the mode of action and safety of these biopesticides on target and non-target organisms
Heart Disease Prediction Using Fuzzy Logic-Based Image Processing and Classification Techniques
Get PDFThe medical field deploys heart disease prediction as a vital operation for early detection to minimize serious health risks. Researchers in this study introduce a new method for heart disease prediction which combines fuzzy logic with image processing together with classification methods. This methodology utilizes fuzzy methods to manage imprecision together with uncertainty found in medical images and numerical information for obtaining more accurate and interpretable outcomes. The initial stage requires fuzzy imputation for handling missing values and fuzzy scaling which transforms features into fuzzy sets for better representation of medical data uncertainties. Define relevant medical imaging regions through fuzzy C-Means clustering before evaluating tissue patterns for heart disease indicators by analyzing these fuzzy texture elements. The combination of fuzzy-genetic algorithms selects significant features through optimized feature space improvements while fuzzy decision trees provide clear means to rank and select features. The system utilizes Mamdani fuzzy inference systems as the final stage to classify heart disease severity based on expert model predictions. Through fuzzy support vector machine implementations the system minimizes data imprecision and overlaps to boost its classification precision. The proposed heart disease prediction method adopts fuzzy machine learning integration to optimize accuracy levels. Image segmentation occurs through Fuzzy C-Means clustering and Local Binary Patterns (LBP) extract texture features before Fuzzy Genetic Algorithms (FGA) select the features. The model received performance evaluation through assessment of its accuracy as well as sensitivity and specificity tests and AUC-ROC metric. The analysis reveals predictive strength through an AUC-ROC value of 0.96 as well as 96.4% accuracy and 93% sensitivity alongside 38% specificity. Cross-validation techniques produced average accuracy of 94% through five-fold validation tests. The integration of fuzzy logic with traditional machine learning proves effective for precise heart disease prediction as it deals effectively with medical data uncertainty and imprecision