年份 | 2017 |
学科 | 机器人与智能机器 Robotics and Intelligent Machines |
国家/州 | United States of America |
Detecting Abnormal Cells Using Artificial Intelligence
Diseases that cause abnormal cells affect millions of individuals. These irregularly shaped cells can be detected visually through a blood smear. A way to automate the detection of abnormal cells using artificial intelligence is necessary as it removes the work for scientists to identify cells and it can lead to more precise results. This system would not require the need for a scientist to analyze the blood smear, so it could be implemented inexpensively in rural places where access to sophisticated medical facilities is limited. For the purposes of this project, sickle cells were used as the abnormal cell. To reach the goal, an application was written in Java to identify sickle cells in images of blood smears using various image-processing algorithms. The application uses a given set of data consisting of the area and circumference of various cell types to generate an algorithm to distinguish sickle cells from healthy cells. The application then analyzes a given blood smear image and processes the detected cells with its own algorithm. It outputs colored rectangular box placed around cells, identifying whether they are healthy red blood cells or sickle cells. The project was concluded developing an application that uses artificial intelligence to develop its own algorithm to distinguish sickle cells from healthy cells. It's planned to expand on this concept by enhancing the program to interface directly with microscopes and detect other diseases. The ultimate goal is to implement this application in places where resources for diagnosing abnormal cell diseases are limited.
英特尔国际科学与工程大奖赛,简称 "ISEF",由美国 Society for Science and the Public(科学和公共服务协会)主办,英特尔公司冠名赞助,是全球规模最大、等级最高的中学生的科研科创赛事。ISEF 的学术活动学科包括了所有数学、自然科学、工程的全部领域和部分社会科学。ISEF 素有全球青少年科学学术活动的“世界杯”之美誉,旨在鼓励学生团队协作,开拓创新,长期专一深入地研究自己感兴趣的课题。
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· 数学 · 物理 · 化学 · 生物 · 计算机 · 工程 ·
Studies in which the use of machine intelligence is paramount to reducing the reliance on human intervention.
Biomechanics (BIE): Studies and apparatus which mimic the role of mechanics in biological systems.
Cognitive Systems (COG): Studies/apparatus that operate similarly to the ways humans think and process information. Systems that provide for increased interaction of people and machines to more naturally extend and magnify human expertise, activity, and cognition.
Control Theory (CON): Studies that explore the behavior of dynamical systems with inputs, and how their behavior is modified by feedback. This includes new theoretical results and the applications of new and established control methods, system modelling, identification and simulation, the analysis and design of control systems (including computer-aided design), and practical implementation.
Machine Learning (MAC): Construction and/or study of algorithms that can learn from data.
Robot Kinematics (KIN): The study of movement in robotic systems.
Other (OTH): Studies that cannot be assigned to one of the above subcategories. If the project involves multiple subcategories, the principal subcategory should be chosen instead of Other.
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