Technical Overview and Evaluation of Heartune App: Mapping Music to Heartbeat for Recreational or Medical Purposes (Whitepaper)

This paper aims to verify the feasibility of utilizing the novel application Heartune as a supplemental treatment for Autism, Alzheimers, Depression/anxiety and developmental delays using passive music therapy. The studies and meta-analyses discussed within this whitepaper illustrate the ability of music therapy in general to benefit the wellbeing and behavioural tendencies of those diagnosed with the aforementioned illnesses, and hence the results obtained by this whitepaper justify the utilization of Heartune as a source for the supplemental treatment for over 100 million patients worldwide. Music therapy has been proven to help several children with developmental delays and Autism especially considering the behavioural changes caused by music therapy. Moreover, the therapy has led researchers to conclude that within the average duration of a song ~3 minutes, the user’s heartbeat can change up to 12%, indicating that the application can be utilised to change the heartbeat and hence the user's mood up to a certain extent. The concluding remarks do state that the application is complementary to the current treatment of the patients and does not in any manner propose a complete recovery from the given illness but proposes to reduce the impacts it has on the lives of the patients.

EMPLOYABILITY OF SELECTED DATAMINING ALGORITHMS IN THE EARLY PREDICTION OF CORONARY DISEASES

The objective of our work is to take apart unique data mining methods and procedures in the healthcare system that can use an assumption for coronary disease structure and their impact investigation. A coronary disease prediction model, which executes the data mining method, can help the therapeutic experts perceive the coronary sickness status subject to the patient's clinical data. Data mining description techniques for the great fundamental initiative in human system are specifically Decision trees, Naive Bayes, Neural Networks and Support Vector Machines. Hybridizing or merging any of these calculations makes decisions snappier and assigned dynamically. Information mining is a notable new improvement for extracting hypermetropic and critical information from enormous data sets to build significant and novel encounters. Using impelled data mining systems to extract essential information has been considered a fanatic method to improve human management organization's quality and precision while trimming down the social protection cost and execution time. Using this technique can expect the early detection of coronary disease. Using more information properties, for instance, could develop controllable and natural danger factors, progressively detailed results. Can also broaden this strategy. It can use an extensive part of data properties. Other data mining strategies use for forecasts, such as clustering, time series plan, and association rules. The unstructured data open in the human system industry information base can mine using content mining.

OVERVIEW OF IMMEDIATE NEW-BORN CHECK-UP

There's proof from maternity hospital-based settings in developing countries that newborn resuscitation education of the staff diminishes new-born deaths from inborn associated events, such as neonatal asphyxia (by 30%), with potential saving 93,700 neonates globally per year by investigating missed attendance of birth clinics or maternity hospitals, together with (up to 192,000) new-born at 90% scope, as it was considering the impact on intrapartum-related neonatal passings. In an arrangement to realize a higher reduction in intrapartum-related newborn passing's, preterm delivery and intrapartum death, a compelling obstetric plan is considered as the most vital intercession and this ought to be complemented with prompt infant care and resuscitation. There is expanding venture in obstetric care, yet to be coordinated by viable execution and supportability of quick infant care and essential newborn resuscitation. Within the private settings, prompt basic care at birth is essential and accessible, even though evaluated by specialists to be of low effects (10% on before delivery and on stillbirths associated with newborn passings). private hospital settingsbased newborn revival may minimise all the reasons of newborn and before delivery deaths, but available information is critical and controversial to directly gauge an effect size from the prove. Future researches ought to endeavour to address impediments distinguished here especially in terms of intercession definitions, plan, comparative control group, outcome identification and subdivision of reasons of stillbirths and neonatal passings. Whereas the available types of evidence for incitement at delivery and neonatal revival are low, mostly since they are regarded as a plan of care, there is adequate and consistent prove of effect. However, such fundamental care stays irregular particularly for the global 60 million home births. Disentangled preparing plan, and effective protocol, low price hardware are presently ac

SKIN SURFACE CHEMISTRY AS A DIAGNOSTIC TOOL FOR SKIN DISEASES

The skin is the biggest sense organ in the body, with a surface area of 1.7m2 in adults. Because standard histological procedures influence skin components, several dermatological research has had little effectiveness in showing skin function. The structure of each skin layer may now be visualised non-invasively thanks to recent advances in non-invasive optical imaging. Individual skin components, on the other hand, remain difficult to identify. Understanding skin's chemical and physical features helps the cosmetics sector create deodorant, lipstick, and moisturizers. In addition, PH regulates the activation of proteases linked to the formation of chronic wounds and impacts skin barrier functions. Optical coherence tomography (OCT) is a non-invasive optical imaging innovation that creates high-resolution photos of the face and cross-areas of the skin. While OCT has a lot of potentials, many dermatologists are unfamiliar with it. This article aims to give professional dermatologists a basic grasp of skin OCT concepts and clinical applications.

EMPLOYABILITY OF ADVANCED IMAGE PROCESSING TO EFFECTIVELY COUNT AND CLASSIFY THE BACTERIAL COLONIES

Specification of Bacterial Colonies is needed in many fields, such as clinical analysis, biomedical examination for anticipation of severe illnesses, and the drug industry to avoid tainting items. Existing Bacterial Colony counter frameworks count Bacterial Colony physically, which is a tedious, less effective and dreary cycle. Henceforth, mechanization for calculating bacterial settlement was required. The proposed strategy counts these settlements naturally utilizing picture handling strategies. This strategy will give a more superior level of precision in the counting of bacterial provinces. The proposed method takes a picture of bacterial settlement and converts it into grayscale. Otsu thresholding is applied for the division of the image, further its change into a double shot. From that point onward, morphological activities are used to tidy up the picture by eliminating commotion and superfluous pixels. Distance and watershed changes are applied to double vision to make parts among covered and joint microscopic organisms. Locale properties and marking data of fragmented picture is utilized for counting of the bacterial province.

ARTIFICIAL BLOOD: AN ACCOUNT OF HBOC AND PFC APPROACHES

In the field of medicine, artificial blood is an innovative concept, where specially designed compounds are developed to perform the task of transport and delivery of oxygen. Hence, it can potentially replace the function of allogenic human blood transfusion. Several molecules have been developed using several approaches. However, with continuous refinements in the past few decades, the ideal blood substitute would likely be Hemoglobin Based Oxygen Carrier. The benefits of HBOCs are tremendous, as they do not require compatibility testing or tissue matching, are non-pathogenic, have a long shelf life, and can even be stored at room temperature. The advent of artificial blood is projected to have a remarkable impact on medical care in the future. While it will complement blood transfusion safely, it will also create a stable supply of effective products. It is likely to reduce the requirements of blood transfusions drastically in settings of surgery, trauma, or warfare.

ROLE OF PANCHTIKTA KSHIRA BASTI IN MANAGEMENT OF AVASCULAR NECROSIS: A CASE STUDY

Avascular necrosis additionally referred to as osteo-necrosis or Ischemic bone necrosis is a condition that occurs when there is a loss of blood supply of bone. An interruption in the blood supply causes bone cells to die. AVN of femoral head is that the commonest sort of necrosis affecting the bone. In Ayurveda, It correlated with asthimajjagata vaat (musculoskeletal disorder). An effort has been made within the present study to gauge the efficacy of panchtikta kshir basti in conservative management of femoral head necrosis of the bone. In Modern medicine, no any unique remedy as opposed to surgical operation is available.

DEVELOPING AN INTEGRATED MODEL BASED ON NAÏVEBAYES AND DECISION TREE ALGORITHMS IN THE EARLY DETECTION AND DIAGNOSIS OF CARDIAC DISEASES

The extraction of concealed information from the enormous data sets is information mining, and it is otherwise called Knowledge Discovery Mining. It has many assignments. One of them utilized here is prescient errands that use a few factors to foresee obscure or future upsides of another dataset. The significant medical issue that influences countless individuals is a coronary illness. Except if it is treated at a beginning phase, it causes demise. Today, the Healthcare business creates an enormous measure of perplexing information about the patients and assets of the emergency clinics, from a period where there has been no good spotlight on compelling examination instruments to find connections in communication, particularly in the clinical area. The methods of mining information are utilized to examine rich assortments of details according to alternate points of view and infer useful data to foster analysis and anticipating frameworks for coronary illness dependent on prescient mining. Various preliminaries are taken up to look at the exhibitions of different information mining procedures, including Decision trees and Naïve Bayes calculations. As proposed, the peril factors are pondered, Decision trees and Naïve Bayes are applied, and the show of their finding have been investigated by the UCI Machine Learning Repository I,e WEKA instrument. Thusly, the Naïve Bayes beats the Decision tree.

LEVERAGING DATA MINING TECHNIQUES IN ENHANCING THE EFFICACY OF HEALTHCARE IN THIRD WORLD COUNTRIES: SPOTLIGHT ON TURKISH CASE STUDY

This paper presents a utilization of the information mining technique to decide the financial profiles of the public clinics in Turkey. The review depends on the information accumulated in 2004, covering 645 public clinics run by the Ministry of Health (MoH) as the fundamental supplier of essential and optional wellbeing administrations in Turkey. The public medical clinics, as of now financed by a combination of assets allotted from the overall spending plan and separately worked rotating reserves, need critical answers for their financial issues as a piece of a continuous public change exertion. The examination takes on the Chi-Square Automatic Interaction Detector (CHAID) choice tree calculation, as one of the most efficient and cutting-edge information digging technique utilized for division. The investigation has discovered that the public clinics could be sorted by the CHAID into 12 unique profiles as far as their financial execution. These profiles have directed us in deciding the key financial markers to be engaged upon in the public emergency clinics and present accepted procedures to work on their individual financial exhibitions. The findings have likewise permitted strategy ideas regarding the financial techniques that might be considered in working on the financial execution of the public medical clinics toward an effective wellbeing area change in Turkey.

AN IN-DEPTH ANALYSIS OF THE IDENTIFIED ALGORITHMS AND THEIR COMPARATIVE STUDY IN THE EARLY DETECTION AND DIAGNOSIS OF BREAST CANCER

These days one of the major inevitable ailments for females is bosom malignancy. The appropriate medication and early findings are important stages to take to thwart this ailment. Although, it's not easy to recognize due to its few vulnerabilities and lack of data. Can use artificial intelligence to create devices that can help doctors and healthcare workers to early detection of this cancer. In This research, we investigate three specific machine learning algorithms widely used to detect bosom ailments in the breast region. These algorithms are Support vector machine (SVM), Bayesian Networks (BN) and Random Forest (RF). The output in this research is based on the State-of-the-art technique.