Title: Optimizing Heuristic Search Algorithms using Neural Networks

Abstract:

Medical Tourism is a fast growing industry which has at least 25% growth globally per year by 2025 (Medical Tourism Magazine, 2015), which is a huge growth comparing to other industries, this definition means that people travel from their countries to another to get their medical care and seeking tourism, it has a remarkable impact and competitive advantage on the other industries with a direct paid services to the health care providers and on the other hand  other countries recognize medical tourism as lucrative opportunity to generate the national income and boost up the economy indirectly enhance the capacity of service providers to handle this type of tourists (AYOUB, 2017). Many challenges are there to appear with each country that include visa issuing, different currencies, international accreditations, language barrier, digital marketing ,cost ,political condition, climate, international insurances (as many patients already covered with international insurances which cover them outside their countries )  branding, country positioning and ranking in medical tourism .

Biography:

Monica Ghazal is an experienced pharmacist by profession and works with more than one of the private international health care facilities in Egypt in the field of medical tourism. She holds a BSc in pharmacy and also Post graduated of Master of Business Administration degree (MBA) major in project management. Monica has 6 years’ experience in pharmaceutical practice and 4 other years in medical tourism industry. She has professional certified trainer from the American university of Cairo also been involved in Digital marketing online and offline branding regarding the field of medical tourism and its inquiries in Egypt. Also completed marketing diploma from Victoria business school she has presented her healthcare group in many international medical tourism events, international associations and embassies. Monica is interested in patient counseling and customer behavior