Dr.professional field focuses on the intersection of healthcare and information technology, and he has also made significant achievements in technology and innovation management. In the medical field, he focuses on the research of the impact of medical analysis, medical safety and medical information technology on chronic diseases, etc. In terms of information technology, I am proficient in social media analysis, data science, etc. Through data mining and analysis, I provide decision support for multiple fields. In the field of technology and innovation management, he is committed to exploring how to promote the effective application and innovative development of technology within the organization and enhance organizational performance.

I once worked as a software development engineer at Amazon, responsible for the design, development and maintenance of software. Served as a data science engineer at Cognitive Cloud Analytics LLC and a data scientist at LLC Conquest Consulting LLC respectively, focusing on the analysis and processing of data. In addition, I have served as a data engineer at Eficens Systems LLC, as a medical informatics research intern at Sanford Imaging, and as an enterprise BI developer at Sanford Health. Currently, he/she serves as an assistant professor of Information Systems and Analytics at the Houghton School of Business at Michigan Technological University. Previously, he/she was a visiting assistant professor (Business Analytics) at the University of Central Oklahoma.

Technical solution

1. Medical data analysis and Application Solutions: Dr.has extensive experience in the field of medical analysis. We can cooperate with medical institutions or medical technology companies to utilize advanced data science and technology to conduct in-depth mining of a large amount of medical data. For example, by analyzing electronic medical record data and establishing a disease prediction model, the risk of chronic diseases can be predicted in advance, helping doctors formulate more effective preventive measures; Analyze medical image data to assist doctors in disease diagnosis and improve the accuracy and efficiency of diagnosis. In terms of medical quality management, the efficiency and quality of medical processes can be evaluated through data analysis, potential problems can be identified and optimization plans can be proposed to enhance the overall service level of medical institutions.

2. Optimization plan for Medical IT Systems: Given his research interests and practical experience in medical IT, the existing information systems of medical institutions can be optimized. For example, optimize the user interface of the Hospital Information Management System (HIS) to make it more in line with the operation habits of medical staff and improve work efficiency; Strengthen the security management of medical data, apply encryption technology and access control mechanisms to ensure the privacy and security of patient data. At the same time, medical Internet of Things (IoT) applications can also be developed to achieve the interconnection and interoperability of medical equipment, monitor the status of the equipment in real time, improve the intelligent level of equipment management, and reduce the equipment failure rate.

3. Social media medical Information Analysis Solution: By integrating professional capabilities in social media analysis, we collaborate with pharmaceutical enterprises and medical research institutions to monitor and analyze medical information on social media. By collecting and analyzing the information such as symptoms and treatment experiences shared by patients on social media, we can understand the epidemic trends of diseases and the needs of patients, providing references for drug research and development and improvement of medical services. In addition, social media can also be utilized to conduct health science popularization and disease prevention publicity, enhance the public's health awareness, and guide correct medical treatment behaviors.

4. Application solutions of Artificial intelligence in the medical and commercial fields: Based on the research of the factors influencing organizations' adoption of artificial intelligence, it can assist enterprises and medical institutions in better applying artificial intelligence technology. In the medical field, develop an artificial intelligence-assisted diagnosis system, utilize machine learning algorithms to learn and analyze medical images and medical record data, and provide diagnostic suggestions for doctors. In the business field, it helps enterprises utilize artificial intelligence to predict customer demands, analyze market trends, optimize marketing strategies, and enhance their competitiveness.