Can an Algorithm Tame Misinformation Online?

June 23, 2017

UCLA researchers are working on an algorithmic solution to the “fake news” problem, we learn from the article, “Algorithm Reads Millions of Posts on Parenting Sites in Bid to Understand Online Misinformation” at TechRadar. Okay, it’s actually indexing and text analysis, not “reading,” but we get the idea. Reporter Duncan Geere tells us:

There’s a special logic to the flow of posts on a forum or message board, one that’s easy to parse by someone who’s spent a lot of time on them but kinda hard to understand for those who haven’t. Researchers at UCLA are working on teaching computers to understand these structured narratives within chronological posts on the web, in an attempt to get a better grasp of how humans think and communicate online.

Researchers used the hot topic of vaccinations, as discussed on two parenting forums, as their test case. Through an examination of nearly 2 million posts, the algorithm was able to come to accurate conclusions, or “narrative framework.” Geere writes:

While this study was targeted at conversations around vaccination, the researchers say the same principles could be applied to any topic. Down the line, they hope it could allow for false narratives to be identified as they develop and countered by targeted messaging.

The phrase “down the line” is incredibly vague, but the sooner the better, we say (though we wonder exactly what form this “targeted messaging” will take). The original study can be found here at eHealth publisher JMIR Publications.

Cynthia Murrell, June 23, 2017

 

Academic Publisher Retracts Record Number of Papers

June 20, 2017

To the scourge of fake news we add the problem of fake research. Retraction Watch announces “A New Record: Major Publisher Retracting More Than 100 Studies from Cancer Journal over Fake Peer Reviews.”  We learn that Springer Publishing Company has just retracted 107 papers from a single journal after discovering their peer reviews had been falsified. Faking the integrity of cancer research? That’s pretty low. The article specifies:

To submit a fake review, someone (often the author of a paper) either makes up an outside expert to review the paper, or suggests a real researcher — and in both cases, provides a fake email address that comes back to someone who will invariably give the paper a glowing review. In this case, Springer, the publisher of Tumor Biology through 2016, told us that an investigation produced “clear evidence” the reviews were submitted under the names of real researchers with faked emails. Some of the authors may have used a third-party editing service, which may have supplied the reviews. The journal is now published by SAGE. The retractions follow another sweep by the publisher last year, when Tumor Biology retracted 25 papers for compromised review and other issues, mostly authored by researchers based in Iran.

The article shares Springer’s response to the matter, some from their official statement and some from a spokesperson. For example, we learn the company cut ties with the “Tumor Biology” owners, and that the latest fake reviews were caught during a process put in place after that debacle.  See the story for more details.

Cynthia Murrell, June 20, 2017

Partnership Hopes to Improve Healthcare through Technology

June 5, 2017

A healthcare research organization and a data warehousing and analytics firm are teaming up to improve patient care, Healthcare IT News reports in, “Health Catalyst, Regenstrief Partner to Commercialize Natural Language Processing Technology.” The technology at hand is the nDepth (NLP Data Extraction Providing Targeted Healthcare) platform, Regenstrief’s specialized data analysis tool. Reporter Bernie Monegain elaborates:

Regenstrief’s nDepth is artificial intelligence-powered text analytics technology. It was developed within the Indiana Health Information Exchange, the largest and oldest HIE in the country. Regenstrief fine-tuned nDepth through extensive and repeated use, searching more than 230 million text records from more than 17 million patients. The goal of the partnership is to speed improvements in patient care by unlocking the unstructured data within electronic health records. Health Catalyst will incorporate nDepth into its data analytics platform in use by health systems that together serve 85 million patients across the country.

In addition, clinicians are contributing their knowledge to build and curate clinical domain expertise and phenotype libraries to augment the platform. Another worthy contributor is Memorial Hospital at Gulfport, which was a co-development partner and was the first to implement the Health Catalyst/ nDepth system.

Based in Indianapolis, the Regenstrief Institute was founded in 1969 with a mission—to facilitate the use of technology to improve patient care. Launched in 2008, Health Catalyst is much younger but holds a similar purpose—to improve healthcare with data analysis and information sharing technologies. That enterprise is based in Salt Lake City.

Cynthia Murrell, June 5, 2017

Linguistic Analytics Translate Doctor Scribbles

May 31, 2017

Healthcare is one of the industries that people imagine can be revolutionized by new technology.  Digital electronic medical records, faster, more accurate diagnostic tools, and doctors having the ability to digest piles of data in minutes are some of the newest and best advances in medicine.  Despite all of these wonderful improvements, healthcare still lags behind other fields transforming their big data into actionable, usable data.  Inside Big Data shares the article, “How NLP Can Help Healthcare ‘Catchup’” discusses how natural language processing can help the healthcare industry make more effective use of their resources.

The reason healthcare lags behind other fields is that most of their data is unstructured:

This large realm of unstructured data includes qualitative information that contributes indispensable context in many different reports in the EHR, such as outside lab results, radiology images, pathology reports, patient feedback and other clinical reports. When combined with claims data this mix of data provides the raw material for healthcare payers and health systems to perform analytics. Outside the clinical setting, patient-reported outcomes can be hugely valuable, especially for life science companies seeking to understand the long-term efficacy and safety of therapeutic products across a wide population.

Natural language processing relies on linguistic algorithms to identify key meanings in unstructured data.  When meaning is given to unstructured data, then it can be inserted into machine learning algorithms.  Bitext’s computational linguistics platform does the same with its sentimental analysis algorithm. Healthcare information is never black and white like data in other industries.  While the unstructured data is different from patient to patient, there are similarities and NLP helps the machine learning tools learn how to quantify what was once-unquantifiable.

Whitney Grace, May 31, 2017

Does This Count As Irony?

May 16, 2017

Does this count as irony?

Palantir, who has built its data-analysis business largely on its relationships with government organizations, has a Department of Labor analysis to thank for recent charges of discrimination. No word on whether that Department used Palantir software to “sift through” the reports. Now, Business Insider tells us, “Palantir Will Shell Out $1.7 Million to Settle Claims that It Discriminated Against Asian Engineers.” Writer Julie Bort tells us that, in addition to that payout, Palantir will make job offers to eight unspecified Asians. She also explains:

The issue arose because, as a government contractor, Palantir must report its diversity statistics to the government. The Labor Department sifted through these reports and concluded that even though Palantir received a huge number of qualified Asian applicants for certain roles, it was hiring only small numbers of them. Palantir, being the big data company that it is, did its own sifting and produced a data-filled response that it said refuted the allegations and showed that in some tech titles 25%-38% of its employees were Asians. Apparently, Palantirs protestations weren’t enough on to satisfy government regulators, so the company agreed to settle.

For its part, Palantir insists on their innocence but say they settled in order to put the matter behind them. Bort notes the unusual nature of this case—according to the Equal Employment Opportunity Commission, African-Americans, Latin-Americans, and women are more underrepresented in tech fields than Asians. Is the Department of Labor making it a rule to analyze the hiring patterns of companies required to report diversity statistics? If they are consistent, there should soon be a number of such lawsuits regarding discrimination against other groups. We shall see.

Cynthia Murrell, May 16, 2017

Medical Records Are the Hot New Dark Web Commodity

January 10, 2017

From emails to Netflix and Uber account information to other personally identifiable information has long been for sale on the Dark Web. A recent article from Fast Company, On The Dark Web, Medical Records Are A Hot Commodity, shares that medical records are the latest offerings for sale on the Dark Web. Medical records sold in these marketplaces usually include an individual’s name, birthdate, social security number and medical information. They fetch the relatively high price of $60 a piece, in comparison to social security numbers at $15. The article explains more,

On the dark web, medical records draw a far higher price than credit cards. Hackers are well aware that it’s simple enough to cancel a credit card, but to change a social security number is no easy feat. Banks have taken some major steps to crack down on identity theft. But hospitals, which have only transitioned en masse from paper-based to digital systems in the past decade, have far fewer security protections in place.

Cybercrime of medical records is potentially life-threatening because oftentimes during the theft of medical records, data showing allergies and other vital information is erased or swapped. Hopefully, the amount of time it took the medical industry to transition from paper to electronic health records is not representative of the time it will take the industry to increase security measures.

Megan Feil, January 10, 2017

Healthcare Technology as a Target for Cyberthreats

December 20, 2016

Will the healthcare industry become the target of cyber threats? Security Affairs released a story, Data breaches in the healthcare sector are fueling the dark web, which explains medical records are among the most challenging data sources to secure. One hacker reportedly announced on the Dark Web he had over one million medical records for sale. The going rate is about $60 per record. According to the Brookings Institute, more than 155 medical records have been hacked since 2009. We learned, 

The healthcare sector is a labyrinth of governance and compliance with risk mitigations squarely focused on the privacy of patient data. We in the industry have accepted the norm that “security is not convenient” but for those in the healthcare industry, inconvenience can have a catastrophic impact on a hospital, including the loss of a patient’s life. Besides patient records, there’s a multitude of other services critical to patient health and wellbeing wrapped by an intricate web of cutting-edge and legacy technologies making it perhaps the most challenging environment to secure. This may explain the rise in attacks against healthcare providers in the last six months.

When it comes to prioritizing secure healthcare technology projects in healthcare organizations, many other more immediate and short-term projects are likely to take precedence. Besides that barrier, a shortage of healthcare technology talent poses another potential problem.

Megan Feil, December 20, 2016

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