2017英特尔ISEF获奖作品摘要 机器人与智能机器（人工智能） Intel Finalist Abstract Robotics and Intelligent Machines (AI)

获奖作品基本信息

年份	2017
学科	机器人与智能机器 Robotics and Intelligent Machines
国家/州	United States of America

获奖作品名称

Utilizing Machine Learning Techniques to Identify Cancerous Skin Lesions

获奖作品摘要

Skin cancer is the most common form of cancer.  When diagnosed early, there is a 98% survival rate.  However, once the cancer metastasizes, the survival rate decreases dramatically to 18%.  The objectives of this study were to (a) use machine learning techniques to better identify the behavior of moles and accelerate the diagnosis of these skin lesions and (b) to minimize the computational cost of training these techniques.  The project included assembling the datasets, building a simple feedforward neural network, and applying different convolutional neural networks.  Additionally, I assembled a workstation to accelerate the neural networks.  My project compared simple feedforward neural networks (FNN) to convolutional neural networks (CNN) in a melanoma image classification task.  I programmed my neural networks in Python using Tensorflow and NVIDIA DIGITS, respectively.

The networks were trained using images subset of the International Skin Imaging Collaboration dataset (ISIC).  The ISIC database has 2000 images that have been collected by dermatologists in an effort to standardize dermatological images.  Three different types of datasets used in machine learning: training, validation, and testing.  The results show the Alexnet CNN outperformed the simple FNN because of its inherent complexity and ability to process images more effectively, at the cost of computational resources.  The simple FNN, which can be trained more quickly, received about 70% accuracy.  The CNN, which required a GPU to accelerate, achieved an 85% accuracy which was better than available programs and close to the 88% accuracy by diagnosis through a dermatologist.

 

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高中生科研学术活动 英特尔 Intel ISEF 简介

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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英特尔 ISEF 学术活动详细介绍

英特尔 ISEF 全程指导方案

· 数学 · 物理 · 化学 · 生物 · 计算机 · 工程 ·

学科简介：机器人与智能机器 Robotics and Intelligent Machines

Studies in which the use of machine intelligence is paramount to reducing the reliance on human intervention.

Subcategories:

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.