2017英特爾ISEF獲獎作品摘要 計算生物與生物信息學(xué) Intel Finalist Abstract Computational Biology and Bioinformatics

獲獎作品基本信息

年份	2017
學(xué)科	計算生物與生物信息學(xué) Computational Biology and Bioinformatics
國家/州	United States of America

獲獎作品名稱

A Non-Invasive Diagnosis Method for Eye Cancers Using Machine Learning Algorithms

獲獎作品摘要

Eye cancer has affected over 500,000 people worldwide in the past decade. Approximately 10% of people with eye cancer will die because it is not diagnosed early enough, causing it to metastasize throughout the body. Fortunately, eye cancer can be treated successfully when it is detected early, and it has a 5-year survival rate of 75%. The aim of this project was to use image processing and machine learning algorithms to develop a system that can correctly categorize an eye tumor as intraocular melanoma, intraocular lymphoma, or retinoblastoma, which are the three most common forms of eye cancer. Image processing algorithms in MatLab were used to analyze the features of a tumor such as asymmetry, border, pigmentation, size, and entropy. Index values were analyzed statistically using a normal distribution curve to better understand the impact of each independent factor. Then, these features were used to program a type of machine learning algorithm called an artificial neural network that can diagnose eye cancer. These comprehensive steps resulted in an algorithm that can diagnose eye cancer with 98% accuracy and can function as preliminary cancer diagnosis. Overall, this program can be used to diagnose 3 different forms of eye cancer non-invasively, and it can potentially save the lives of thousands of people who die from this cancer each year.

---

高中生科研 英特爾 Intel ISEF
資訊 · 課程 · 全程指導(dǎo)
請掃碼添加微信好友

[vc_btn title="聯(lián)系電話：(021) 63526628" color="black" align="center" css_animation="fadeIn" link="url:tel%3A02163526628||target:%20_blank|rel:nofollow"]

---

ISEF 簡介

英特爾國際科學(xué)與工程大獎賽，簡稱 "ISEF"，由美國 Society for Science and the Public（科學(xué)和公共服務(wù)協(xié)會）主辦，英特爾公司冠名贊助，是全球規(guī)模最大、等級最高的中學(xué)生的科研科創(chuàng)賽事。ISEF 的學(xué)術(shù)活動學(xué)科包括了所有數(shù)學(xué)、自然科學(xué)、工程的全部領(lǐng)域和部分社會科學(xué)。ISEF 素有全球青少年科學(xué)學(xué)術(shù)活動的“世界杯”之美譽，旨在鼓勵學(xué)生團隊協(xié)作，開拓創(chuàng)新，長期專一深入地研究自己感興趣的課題。

>>> 實用鏈接匯總 <<<

英特爾 ISEF 學(xué)術(shù)活動詳細介紹

英特爾 ISEF 全程指導(dǎo)方案

· 數(shù)學(xué) · 物理 · 化學(xué) · 生物 · 計算機 · 工程 ·

學(xué)科簡介：計算生物與生物信息學(xué) Computational Biology and Bioinformatics

Studies that primarily focus on the discipline and techniques of computer science and mathematics as they relate to biological systems. This includes the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavior, and social systems.

Subcategories:

Computational Biomodeling?(MOD):?Studies that involve computer simulations of biological systems most commonly with a goal of understanding how cells or organism develop, work collectively and survive.

Computational Epidemiology (EPD):?The study of disease frequency and distribution, and risk factors and socioeconomic determinants of health within populations. Such studies may include gathering information to confirm existence of disease outbreaks, developing case definitions and analyzing epidemic data, establishing disease surveillance, and implementing methods of disease prevention and control.

Computational Evolutionary Biology?(EVO):?A study that applies the discipline and techniques of computer science and mathematics to explore the processes of change in populations of organisms, especially taxonomy, paleontology, ethology, population genetics and ecology.

Computational Neuroscience?(NEU):?A study that applies the discipline and techniques of computer science and mathematics to understand brain function in terms of the information processing properties of the structures that make up the nervous system.

Computational Pharmacology?(PHA):?A study that applies the discipline and techniques of computer science and mathematics to predict and analyze the responses to drugs.

Genomics?(GEN):?The study of the function and structure of genomes using recombinant DNA, sequencing, and bioinformatics.

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.