UHD REU Program > Project Description
1. Experimentation with a Modified Dijkstra’s Algorithm -- Providing Physical Layer Security to an All Optical Network
Mentor: Dr. Shengli Yuan
2. Cascaded Classifier for Automatic Crater Detection
Mentor: Dr. Tomasz Stepinski, Dr. Wei Ding
Henry Z. Lo
3. Coreference Resolution in Clinical Texts
Mentor: Dr. Ping Chen
Students: David Hinote and Carlos Ramirez
The 2011 I2B2 challenge involves co-reference resolution in medical documents. Concept mentions have been annotated in clinical texts, and the mentions which co-refer in each document are to be linked by co-reference chains. Normally, there are two ways of constructing a system to automatically discover co-referent links. One is to manually build rules for co-reference (a rule based approach), and the other is to use machine learning systems to build the rules automatically (a machine learning approach). There have been systems developed for co-reference resolution by various organizations. The aim of this study was to use the systems which are publicly available, as well as build a system tailored for this challenge using a rule based system, and test these systems on the data provided for this challenge. The study shows the publically available systems do manage to find some of the co-referent links, and the rule based system developed for this challenge performs well finding the majority of the co-referent links. The system that was used to provide the final outputs for the challenge had 89.6% overall performance average.
4. Brain State Analysis
Mentor: Dr. Hong Lin
Student: Tremaine A. Rawls
The primary objective for this summer research project is to analyze the Electroencephalography (EEG) data, brain waves statistics, in order to develop models to differentiate different brain states. This project aims to read these brainwaves when a person is in meditation state, allowing us to decipher the difference between a person in mediation and a person who is not. Since the brain is an electrochemical organ using electromagnetic energy to function, electrical activity emanates from the brain and can be displayed in the form of brainwaves when the data is rendered and configured accordingly. The brain wave analyzer contains 14 different nodes that are scattered across the four main sections of the brain (frontal lobe, thalamus, parietal lobe, and reticular formation) that picks up on different types of brain waves, alpha, beta, delta, and theta waves. The EEG data is being collected from our collaborators Dr. Wanli Ma and Dr. Dat Tran at the University of Canberra, Australia, and Dr. Beyongsang Oh at the University of Sydney. The Graphical system will include several elements that permit the information to be read into the program, and modified as needed. The brain wave analyzer will be the basis for distinguishing key distinctions in each node at any given frame to interpret brain states and analyze them. Final Presentation: Brain State Analysis
5. UMLS Word Search
Mentor: Dr. Ping Chen
Student: Brian Ng
My objective for summer research is to find terms in documents based on human anatomical structures found in the human body. The terms in the documents will be compared to a database of terms that Unified Medical Language System (UMLS). The main focus for developing a log of the terms of the UMLS. The next stage was using a high level computer language like Java to do the simple comparison of words taken from an external source to the log of terms from the UMLS. When a first term of a UMLS word or phrase is located and they are equivalent. Tools to aid in searching for terms will be regular expressions and sample papers. These tools help to aid in accuracy for finding words and therefore improves the overall results to a person using the program. The next word for comparison is taken and compared to the next word of the phrase. When all words are equivalent a counter is updated and the word found is printed to the screen. The program will be refined to obtain better accuracy and recall throughout the summer or for a specific end product. After optimization, the rest of the time spent will be on how the words can be displayed either in another text document with tags for the words found or an interface showing connection of the word to a 3D model of the human body. By summers end, I will be more competent in coding and searching for expressions.
6. Information Extraction from Medical Extraction
Mentor: Dr. Ping Chen
Student: Alexander Barsky
Using GATE (General Architecture for Text Engineering), we are attempting to extract valuable information from patient's charts and organize the information in a coherent manner. Generally a patient's chart is heavily documented. This makes locating important information difficult and time consuming. Using the latest techniques in pattern recognition, data mining, co-referencing and other, we are attempting to pinpoint the information we need quickly and efficiently. We are utilizing JAPE grammar rules to establish the parameters that are necessary to extract information to obtain an accurate, concise picture of a person's medical information. After we have the final annotated documents, GATE outputs the document in XML format. We use C# in conjunction with XLST stylesheets to strip the XML documents of all superfluous data. This is done so that the data can be presented in an easily understandable format. Also it allows for simple and quick data manipulation. While information extraction through JAPE grammar allows us to retrieve an accurate portion of necessary information, it does have a few setbacks. No matter how many specific grammar rules are written for extraction, there will always be necessary information left out. This is not acceptable when a patient's medical history is to be considered. The best method to remedy this is through machine learning. We are using WEKA to add classifications to the project. This is only the first step to attempt to utilize machine learning as it is still in its elementary stages of practical usage.
7. Investigation of a 3D Simulation Model
Mentor: Dr. Ongard Sirisaengtaksin