Select a problem using knowledge, reasoning, and/or planning that may arise in the real world. Examples include expert system, automatic theorem proving, knowledge and reasoning applications, etc).Alternatively, you may select a development in AI where these are utilized._ out of 10 points Describe the knowledge, reasoning, and/or planning problem used (based on methods discussed in class, including logical agents, first-order logic, classical planning, scheduling, knowledge representation, etc) out of 10 points
Design and describe the algorithm and approach of your implementation. You may create visual representations and include a description.You may also implement your own code or pseudocode if you feel that may help demonstrate your understanding_____ out of 20 points
Please include references for your sources.
Explain why you selected your chosen method(s). _ out of 20 points Explain how your chosen method would help solve your chosen problem. Think about the how the problem/application is formulated, model representations used, logics, languages for representing problems, algorithms, etc.Your project could also comprise of integration of various AI approaches (probabilistic logic, planning, reasoning, etc). Describe the strengths and limitations. out of 10 points
Describe what may have been some alternative methods. out of 10 points Describe what methods may not have been appropriate out of 10 points
Describe what you learned from this assignment, what could be improved, and what could be some future extensions of your work _ out of 10 points
NCEP/ATPIII definition for children 12-18 years: Individuals with ≥3 of the following are considered at risk for MS: -Waist circumference ≥90th Percentile for age and sex – HDL cholesterol ≤40 mg/dl, -Triglycerides ≥110 mg/dl – Fasting plasma glucose >110 mg/dl, and -BP ≥90th percentile according to age and sex Waist circumference percentiles for the Indian Population were published recently by Khadilkar et al (18). They have suggested a cut-off of 70th percentile for WC, to screen for Metabolic Syndrome in Indian children. 5. Nonalcoholic Fatty Liver Disease (NAFLD): Nonalcoholic fatty liver disease (NAFLD) constitutes a spectrum of conditions, ranging from steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis, in the absence of excessive alcohol consumption. The prevalence of NAFLD is 34.2% in obese children & adolescents and the reported prevalence is highest in Asia (19). Most children are asymptomatic, while some may complain of right upper quadrant pain or abdominal discomfort. NAFLD aggravates hepatic insulin resistance, thereby increasing the risk of developing T2DM. The liver SAFETY (Screening ALT for Elevation in Today’s Youth) study was conducted to develop ALT thresholds and the cut-off of ALT >25 for boys and >22 for girls were suggested for screening NAFLD in children (20). 6. Polycystic Ovary Syndrome (PCOS): Increased adiposity, especially abdominal, is associated with hyperandrogenemia and increased metabolic risk. The diagnosis of PCOS in an adolescent girl should be made based on the presence of clinical and/or biochemical evidence of hyperandrogenism (after exclusion of other pathologies) in the presence of persistent oligomenorrhea (21). Polycystic ovary morphology on ultrasound is not reliable to make a diagnosis in adolescents because multi-follicular ovaries are a feature of normal puberty that subsides with onset of regular menstrual cycles (22). 7. Psychiatric: Results from several studies suggest a higher rate of depression among obese children than among children of normal weight. In addition to depression, anxiety and low-self esteem have also been found to relate to obesity in children and adolescents. A study by Grilo et al. (23) demonstrated that “the greater the frequency of being teased about weight and shape while growing up, the more negative one’s appearance is regarded, and the greater the degree of body dissatisfaction in adulthood”. 8. Miscellaneous: Orthopedic problems, such as slipped capital epiphyses and Blount’s disease, occur in obese children. Approximately 50% to 70% of children with slipped capital epiphyses are obese. Obese children are also at a higher risk for developing gall stones, pseudotumor cerebri and obstructive sleep apnea. EVALUATION OF THE OBESE CHILD:>GET ANSWER