Internal Medicine


Machine Learning and Evidence-Based Medicine Annals of Internal Medicine

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Inferences were made using traditional biostatistics. In the early 1990s, ML emerged, whereby advanced computing programs (machines) processed huge data sets (big data) from many sources and discerned patterns among multiple unselected variables. Such patterns were undiscoverable using traditional biostatistics (1) and were used to iteratively refine (learn) layered mathematical models (algorithms). The Table lists key differences between EBM and ML.


Predicting C. Diff Risk with Big Data and Machine Learning

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A new model analyzes a wealth of information to better predict which patients are more prone to the dangerous infection. Nearly 30,000 Americans die each year from an aggressive, gut-infecting bacteria called Clostridium difficile. Resistant to many common antibiotics, C. diff can flourish when antibiotic treatment kills off beneficial bacteria that normally keep the deadly infection at bay. But doctors often struggle to determine when to take preventive action. New machine learning models tailored to individual hospitals could offer a much earlier prediction of which patients are most likely to develop C. diff, potentially helping stave off infection before it starts.


Dating app Grindr says it will stop sharing HIV status, profile info with other companies

USATODAY

An error on the dating app Grindr allowed third party sites to access personal information. Tony Spitz has the details. Dating app Grindr, which serves many LGBTQ users, admits it has been sharing users' HIV status with third-party companies. Grindr says it will stop sharing user data, including HIV status, to two other companies, after concerns the disclosures violated consumer privacy and undermined public health efforts. The gay dating and social networking app, which counts over 3 million daily active users, said Tuesday it would no longer share users' HIV status with app optimization company Apptimize and is discussing how to remove data from Localytics.


Grindr to stop sharing HIV status of users with third-party companies after fierce criticism

The Independent

Gay dating app Grindr has said it will stop sharing its users' HIV status with other companies after it was heavily criticised for distributing the information to third parties. Tech firms Apptimize and Localytics, which help to manage the app's performance, had been provided with the data. As the HIV information is transferred alongside GPS, phone ID data, and email, users could be identified along with their HIV status, according to Antoine Pultier, a researcher at Norwegian non profit organisation, SINTEF, which first raised the issue. In response, Grindr's chief technology officer, Scott Chen, said sharing data with partners to test and optimise its platform was "industry practice". He insisted sensitive data was encrypted when sent and vendors were bound by strict contractual terms to ensure it is kept secure and confidential.


Gay dating app Grindr changes its policy of sharing users' HIV status with outside vendors

Los Angeles Times

Grindr was confronted with questions about security flaws as recently as last week after NBC reported private information about users, including unread messages, deleted photos and location data, were being collected by a property management startup through a website that Grindr built. Grindr says it has since fixed the flaw and shut down the website, which allowed users to see who blocked them on the app.


Gay Dating App Grindr Shared HIV Status With Other Companies

U.S. News

Grindr says Localytics and Apptimize were paid to test and monitor how the app is used. The company says the firms are under "strict contractual terms that provide for the highest level of confidentiality, data security and user privacy." Grindr says data that may include location or information from HIV status fields are "always transmitted securely with encryption."


Self-driving Uber death should halt tech's race to the bottom

New Scientist

Around the world, vehicles kill more people than HIV/AIDS – about 1.3 million each year. In the vast majority of cases, it is the inattentive and error-prone humans operating those cars and lorries who are at fault. Pedestrian Elaine Herzberg died after being struck by an autonomous Uber car on Sunday as she crossed a road – the first time that a self-driving vehicle has claimed the life of another road user.


To Fight Fatal Infections, Hospitals May Turn to Algorithms

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The technology used by Facebook, Google and Amazon to turn spoken language into text, recognize faces and target advertising could help doctors combat one of the deadliest killers in American hospitals.


Artificial Intelligence, False Gods, and Driverless Everything

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Today the field has progressed to the point where algorithms can recognize photos, speech and emotions, fly a drone or drive a truck, spot early signs of diabetes or cancer, and play chess and poker at a championship level. Now, in a leap that could be futuristic, absurd, or life-changing (nobody can predict which), the vision is of a robotics religion that worships an AI godhead. Anthony Levandowski, known for his contribution to driverless cars and a pioneering visionary of AI, gained wide media attention by actually forming an AI church named The Way of the Future. He is searching for adherents, and foresees an AI godhead as not ridiculous but inevitable. As he told an interviewer from Wired magazine, ""It's not a god in the sense that it makes lightning or causes hurricanes.