首页
外语
计算机
考研
公务员
职业资格
财经
工程
司法
医学
专升本
自考
实用职业技能
登录
外语
It’s Hard to Clean Big Data A)Karim Keshayjee, a Toronto physician and digital health consultant, crunches mountains of data fro
It’s Hard to Clean Big Data A)Karim Keshayjee, a Toronto physician and digital health consultant, crunches mountains of data fro
admin
2014-12-26
22
问题
It’s Hard to Clean Big Data
A)Karim Keshayjee, a Toronto physician and digital health consultant, crunches mountains of data from 500 doctors to figure out how to improve patient treatment. But it’ s a frustrating slog to get a computer to decipher all the misspellings, abbreviations, and notes written in unintelligible medical shorthand.
B)For example, "smoking information is very hard to parse," Keshayjee said. "If you read the records, you understand right away what the doctor meant. But good luck is trying to make a computer understand. There’s ’never smoked’ and ’smoking = 0.’ How many cigarettes does a patient smoke? That’ s impossible to figure out."
C)The hype around slicing and dicing massive amounts of data, or big data, makes it sound so easy: Just plug a library’ s worth of information into a computer and wait for valuable insights to pour out about how to speed up an auto assembly line, get online shoppers to buy more sneakers, or fight cancer. The reality is much more complicated. Data is inevitably "dirty" thanks to obsolete, inaccurate, and missing information. Cleaning it up is an increasingly important and overlooked job that can help prevent costly mistakes.
D)Although techniques are improving all the time, scrubbing data can only accomplish so much. Even when dealing with a relatively tidy set of information, getting useful results can be arduous and time-consuming. "I tell my clients that the world is messy and dirty," said Josh Sullivan, a vice president at business consulting firm Booz Allen who handles data crunching for clients. "There are no clean data sets."
E)Data analysts start by looking for information that’ s out of the norm. Because the volume of data is so huge, they typically hand the job over to software that automatically sifts through numbers and text to look for anything unusual that needs further review. Over time, computers can improve their accuracy in spotting what’ s belongs and what doesn’t. They can also better understand what words and phrases mean by clustering similar examples together and then grading their interpretations for accuracy. "The approach is easy and straightforward, but training your models can take weeks and weeks," Sullivan said.
F)A constellation of companies offer software and services for cleaning data. They range from technology giants like IBM IBM -0.24% and SAP SAP 0.12% to big data and analytics specialists like Cloudera and Talend Open Studio. A legion of start-ups is also trying to get a toehold as data janitors including Trifacta, Tamr, and Paxata.
G)Healthcare, with all its dirty data, is one of the toughest industries for big data technology. Electronic health records make medical information increasingly easy to dump into computers, but there’ s still a lot room for improvement before researchers, pharmaceutical companies and hospital business analysts can slice and dice all the information they want.
H)Keshavjee, the doctor and CEO of InfoClin, a health data consulting firm, spends his days trying to tease out ways to improve patient treatment by sifting through tens of thousands of electronic medical records. Obstacles pop up all the time.
I)Many doctors neglect to note a patient’ s blood pressure in their medical records, something that no amount of data cleaning can fix. Simply determining what ails patients—based on what’ s in their files—is surprisingly difficult for computers. Doctors may enter the proper code for diabetes without clearly indicating whether it’ s the patient who has the disease or a family member. Or they may just enter "insulin" without mentioning the underlying diagnosis because, to them, it’ s obvious.
J)Physicians also use a lot of idiosyncratic shorthand for medications, illnesses and basic patient details. Deciphering it takes a lot of head scratching for humans and is nearly impossible for a computer. For example, Keshavjee came across one doctor who used the abbreviation"gpa." Only after coming across a variation, "gma," did he finally solve the puzzle—they were shorthand for "grandpa" and "grandma."?"It took a while to figure that one out," he said.
K)Ultimately, Keshavjee said one of the only ways to solve the problem of dirty data in medical records is "data discipline." Doctors need to be trained to enter information correctly so that cleaning up after them is less of a chore. Incorporating something like Google’ s helpful tool that suggests how to spell words as users type them would be a great addition for electronic medical records, he said. Computers can learn to pick out spelling errors, but minimizing the need is a step in the right direction.
L)Another of Keshavjee’ s suggestions is to create medical records with more standardized fields. A computer would then know where to look for specific information, reducing the chance of error. Of course, doing so is not as easy as it sounds because many patients suffer from multiple illnesses, he said. A standard form would have to be flexible enough to take such complications into account.
M)Still, doctors would need to be able to jot down more free-form electronic notes that could never fit in a small box. Nuance like why a patient fell, for example, and not just the injury suffered, is critical for research. But software is hit and misses in understanding free-form writing without context. Humans searching by keyword may do a better job, but they still inevitably miss many relevant records.
N)Of course, in some cases, what appears to be dirty data, really isn’t. Sullivan, from Booz Allen, gave the example the time his team was analyzing demographic information about customers for a luxury hotel chain and came across data showing that teens from a wealthy Middle Eastern country were frequent guests. "There were a whole group of 17 year-olds staying at the properties worldwide,’ Sullivan said. "We thought, ’ That can’ t be true.’ "
O)But after some digging, they found that the information was, in fact, correct. The hotel had legions of young customers that it didn’t even realize were there, and had never done anything to market to them. All guests under 22 were automatically logged as "low-income" in the company’s computers. Hotel executives had never considered the possibility of teens with deep pockets.? "I think it’s harder to build models if you don’t have outliers," Sullivan said.
P)Even when data is clearly dirty, it can sometimes be put to good use. Take the example, again, of Google’ s spelling suggestion technology. It automatically recognizes misspelled words and offers alternative spellings. It’s only possible because Google GOOG -0.34% has collected millions and perhaps billions of misspelled queries over the years. Instead of garbage, the dirty data is an opportunity.
Q)Ultimately, humans, and not machines, draw conclusions from the data they crunch. Computers can sort through millions of documents, but they can’ t interpret the findings. Cleaning data is just one of step in a long trial and error process to get to that point. Big data, for all its hype about its ability to lift business profits and help humanity, is a big headache. "The idea of failure is completely different in data science," Sullivan said. "If they don’t fail 10 or 12 times a day to get to where they should be, they’re not doing it right."
Software can hardly understand free-form writing written by doctors without any background information.
选项
答案
M
解析
题干意为如果不提供任何背景信息,电脑软件很难理解医生所写的自由行文的病例。根据题干中的“free-form writing”可定位至M段“But software is hitand misses in understanding free-form writing without context.”.题干是对该句的同义转述,其中,“can hardly understand”和“background information”分别与原文中的“ishit and misses in understanding”和“context”相对应。
转载请注明原文地址:https://kaotiyun.com/show/Zoh7777K
0
大学英语六级
相关试题推荐
A、Howprivatelanguagesaredeveloped.B、Howancientpeoplecreatedlanguages.C、Theassociationsbetweendifferentlanguages.D
Americansareahighlymobilepeople.Whatfactorscausethemtomove?The(36)______foreconomicbettermentisgenerallythemos
Americansareahighlymobilepeople.Whatfactorscausethemtomove?The(36)______foreconomicbettermentisgenerallythemos
A、Theyfounditdifficulttocommunicatewithteachers.B、Theyfounditdifficulttoadapttothenewenvironment.C、Theycan’t
Themobilephoneissettobecomeoneofthecentraltechnologiesofthe21stcentury.Withinafewyears,themobilephonewill
Respectbeginswithintheindividual.Theoriginalstateofrespectisbasedonawarenessoftheselfasaunique(36)_____.The
A、Hecangetmorefreshair.B、Thelocalpeopleareveryfriendly.C、Hecanescapethedullcitylife.D、Thingsaremuchcheaper
A、Deathscausedbytheproblemincreased80%in2004.B、Theproblemcausedalmost20,000deathsin2004.C、Theproblemranksthe
A、Statesmustsetahigherminimumwagethanunderfederallaw.B、Statesmustforbidsmallcompaniestosetalowminimumwage.
A、ShelivesinasmalltowninWales.B、Shelivesinadensely-populatedcountry.C、Onlyasmallnumberofpeopleknowherhome.
随机试题
对诊断原发性肝癌具有较高特异性的检查是()
营养性维生素D缺乏性手足搐搦在痉挛发作时哪项处理最正确
某机关办公楼会议室需进行装饰装修,该办公室层高4.5m,吊顶高度2.6m.装饰设计要求采用轻钢龙骨双层石曹板吊顶,局部人造饰面板造型吊顶,顶棚内含有路管线。施工中对人造饰面板的内、外表面以及相应木龙骨涂覆了一级饰面型防火涂料。该办公楼共有会议室6间,每间面
根据婚娴家庭法律制度的规定,下列关于婚姻无效和可撤销婚姻的表述中,正确的有()。
下列会计事项中,应在其他业务成本科目核算的有()。
根据营业税法律制度的规定,下列各项中,应当征收营业税的有()。
规定“国家将整体设置九年一贯制义务教育课程”“学校和教师不得公布学生考试成绩和按考试结果公开排队”的文件是
(2015年真题)近年来,全国每年发生交通事故40多万起,近10万人死亡。司机的酒驾、超载和超速驾驶,行人无视红绿灯的“中国式过马路”等行为都是导致交通事故发生的重要原因。西方思想家曾言,最重要的法律,既不是刻在大理石上,也不是刻在铜表上,而是铭
下列关于综合布线系统的描述中,错误的是()。
书写查询条件时,日期值应该用()括起来。
最新回复
(
0
)