Attention Deficit Hyperactivity Disorder (ADHD) is the most frequent brain disorders in children. Brain is the greatest complicated data processing part in human body. ADHD can begin in childhood age and may extend till adolescent too. ADHD patients activities/actions/behaviour are totally different from non ADHD patients. To solve the problem in early stage is more precious contribution for children life. Otherwise the disorder may cause further destruction in child brain. An activity of ADHD child is: carelessness, impulsive, and feverish. These activities may be common in other children too but for ADHD patients these activities are more severe and more often occurs. ADHD can arise problems at school, home, it may affect children learning ability, and child may not join with others. ADHD is one among many childhood syndromes. The paper summarises the different ADHD diagnosis methods and suggested treatments for the disorder.
Research into the impact of in Vitro Fertilization (IVF) enables customer systems is still in its infancy. Our method represents a tool to support decision making for patient analysis with fertility problems whether the patient will conceive or not. An in-depth formative evaluation of the essential attributes which are necessary for the IVF treatment are achieved by data collection (data set), data pre-processing, a model formulation which includes applying of the three supervised ML techniques namely, Multinomial Naive Bayes, Random Forest, Decision Tree which predicts the accuracy and then followed by uploading the patient records into the cloud. There were 28 attributes used to build the project. The results obtained by using these three algorithms are 62.41% for multinomial Naive Bayes, 69.14% for the random forest, and 41.31% for decision tree. IVF patients seek support from the real-time web based decision support system by using machine learning and AWS cloud services to know the accuracy, retrieving, and uploading the patient records to the on demand cloud service platform. More research is needed to inform the real-time web based disease decision support system design that effectively tailors support for patient's wellbeing.
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