About 7-11% of children in the ages between 4 and 17 are diagnosed with Attention Deficit Hyperactivity Disorder (ADHD). Despite this alarming rate and its deleterious effects on children in the academic as well as social settings, the current research in designing for ADHD is found wanting. The study here seeks to delve in depth about the need for designers to develop domain knowledge about ADHD, some key points to keep in mind while designing for children as well as evaluating the current applications in terms of how they cater to their ADHD audience, culminating by offering a design-thinking approach which could help alleviate some of the aforementioned flaws.

Changes in lifestyle have followed the path of development in the materialistic world and so have brought many causes for development of various disorders which are related to this new world. In the modern era of globalisation and development, due to stressful lifestyle and lack of self-observation we are facing several challenging lifestyle disorders like Diabetes mellitus, Hypertension, Atherosclerosis, Heart disease, stroke and obesity to which modern medicine has no appropriate answer. In this field, the world’s oldest life science Ayurveda gives a proven, fundamental solution in the form of Panchkarma. Ayurveda is with the important motives of protecting the healthy state of a healthy person and curing the disease. Thus it serves both purposes, preventive and curative. Panchkarma is the important path to serve the purposes. Panchkarma includes five major procedures that are designed for bio purification in both healthy as well as diseased states of body. Panchkarma means ‘five actions’ or ‘five elements’.Since it consists of five main therapies it is named so. It has been given a special place in all ancient ayurvedic texts. It includes five specific bio purification processes namely Vamana, Virechana, Basti, Nasya and Raktamokshana. In Ayurveda the balance of tridosha in the body is health and their imbalance in body is disease. So, Panchakarma is not only good for alleviating diseases but it is also useful tool in maintaining excellent health.

Bread is most critical, reasonable and simple eating nourishment which appeared a great many years back (Shahnawaz,et al.,2012). Bread is known to be the introduction of bakery product which is also a successful experiment by Egyptians over 12000 BC. It is known to be the most convenient and accepted food in the world (Udeme Joshua Josiah Ijah, et al., 2014). There are so many varieties of bread present in market that are claiming to be healthy one after the other and many companies claims that the recipe is simple (wheat flour, water, salt, sugar, oil and yeast) and the use of wheat flour in some amount will not harm the human (Lilleberg,2012). There are many flours that are incorporated now days so wholesome substance of the sustenance can be upgraded and furthermore the infections that are influencing individuals can be limited with the utilization of good alternatives than utilizing the same. In this way the present investigation is focussed on the utilization of curry leaves powder in bread to expand its healthful incentive as it is a rich source of different vitamins, minerals, cancer prevention agent and assortment of other fundamental supplements

One of the major across the board infection nowadays for ladies is breast cancer. the right treatment and early detection is a significant advance to take to forestall this ailment. notwithstanding, it is difficult, due to a couple of vulnerabilities and acknowledgment of mammograms. AI (ML) techniques can be helpful in making mechanical assemblies for specialists that can be further useful as a framework for the early stage detection and eliminating some of breast malignant growth development which will essentially improve the endurance pace of patients. This paper investigation around three of the most conspicuous ML techniques by and large used for breast disease area and finding, specifically Support Vector Machine (SVM), Random Forest (RF) and Bayesian Networks (BN). The Wisconsin bosom disease threat educational assortment was used as planning set to survey and consider the execution of the three ML classifiers to the extent key parameters, for instance, precision, audit, exactness, and zone of ROC. The results got right now a diagram of the state of craftsmanship ML strategies for chest development recognizable proof.

Breast Cancer is the prime reason for death in Indian ladies. Medical clinics in India utilize electronic methods for assortment and detailing of information. One such report is the Pathology report which has regular language portrayals of the states of patients. This work plans to extricate the subtleties on Tumour (T) in the bosom utilizing design coordinating standards and determine the neurotic characterization of T by applying the PTNM arrangement convention by American Joint Committee on Cancer (AJCC). Data Retrieval (IR), Natural Language Processing (NLP) undertakings and Information Extraction (IE) strategies are applied to build up a mechanized framework to achieve the errand. The framework investigates the removed and the ordered estimations of T against the Gold Standard Values, which are inferred by manual examination of the reports. The assessment of the exhibition of the computerized framework performed utilizing three arrangements of Pathology reports, brought about a normal Precision of 86%, Recall of 82.7%, Specificity of 75.1% and Accuracy of 79.53%.

These days, there are a vast number of endorsed drugs that can be utilized for treating individuals who have clinical issues. Consequently, drug alerts and insurances are meant to perceive a discrete arrangement of antagonistic impacts and other inferred assurance vulnerabilities that are helpful for quite a control. In this investigation, the planned system is isolated into two chief stages: information recovery and information handling. Right off the bat, in the information assortment stage, drug reports, drug connections, glitches, number of passing’s, and different variables had been acquired from different references, including RxNorm and Drug Bank utilizing web administration. Furthermore, in the information handling stage, distinctive information mining calculations used to group drugs into appropriate medications and non-reasonable medications. As indicated by the test results, we found that the choice tree has more exactness (97.9%) than other condition of-craftsmanship techniques.