Dmitriy Shin, MS
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Clinical Instructor
phone: 573-882-6940
email: shindm@missouri.edu
Biographical sketch
Degrees: MS, Computer Science, Moscow State Academy of Computer Science and Engineering, Moscow, Russia
Additional study: Doctoral program in biomedical informatics, University of Missouri Informatics Institute, Columbia, Missouri
Academic appointments:
Clinical Instructor, Department of Pathology and Anatomical Sciences, School of Medicine, University of Missouri Health Sciences Center, Columbia
Interests:
- biomedical informatics
- computational cancer biology
- machine learning and data mining
- computational intelligence (neural networks, fuzzy systems, swarm intelligence and evolutionary computation)
Research description: Dmitriy Shin is studying complex computational methods in biomedical domain, including digital pathology and cancer biology. His main reserach interests are in the area of computational intelligence, data mining, pattern recognition and machine learning.
Currently he is working on computational methods for determining the identification of antibody panels for the classification of lymphomas that will provide an optimally efficient diagnostic path. This research direction, reffered as "morphoproteomics", is a part of a new emerging subfield of pathology described as"systems pathology". The work is done in collaboration with Drs. Arthur, Shyu, Anthony and Caldwell.
Another collaborative effort is the data mining studies of gene expression and DNA methylation data provided by the Dr. Caldwell's epigenetic lab. This project included using radial basis function afrtificial neural networks as well as genetic algorithms to discover hidden finctional interrelationships among different gene expression and DNA methylation profiles in the form of association rules. The work is primarily done on lymphoma datasets.
Dmitriy Shin has also been working in other areas of biomedical informatics. He collaborates with Dr. Mariuis Petruc on studying factors that influence the quality of radiology imaging investigations using computational models. Another collaboration between Dmitriy Shin and Dr. Marius Petruc is the study of telemedical methods to encourage positive behavioral patterns in type I diabetes pediatric patients, where they are co-principal investigators. The research is funded by the Children's Miracle Network grant. For this study, Dmitriy Shin has designed a long range wireless transmitter device that allows blood glucose data to be remotely sent to the processing center where they are analyzed using machine learning and computational intelligence methods. The telemedical methods encouraging positive behavior in diabetes patients includes system initiated reminders and alerts that are generated based on complex analysis of blood glucose, Hemoglobin A1c (HbA1c) and other measurements and delivered to patients using cutting edge Text-To-Speech and Voice-over-IP technologies.
Representative Publications:
- “A Telemedical Approach to Encourage Positive Behavioral Patterns in Type 1 Diabetes Pediatric Patients” Children’s Miracle Network grant.
- “Using association rules mining of pathology reports to assess the interpretation accuracy of imaging investigations”.
- “Data mining and modeling of WNT signaling pathways and gene methylation data in Chronic Lymphocytic Leukemia and NHL cases”
- “Analysis of Different Fuzzy Operators and their Independent Parameters in Multicriteria Medical Diagnosis Based on Borderline Values”.
- “Automatic Discovery of Regular Expression Patterns Representing Negated Findings in Medical Narrative Reports".
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