Apple is launching a new app for consumers to sign up for up to three new medical studies.
The app, dubbed Research, will be available to download via the Apple Store on Thursday. People can ask to participate in studies on heart, movement and hearing issues, and on women’s health. Those who meet the criteria will be asked to stay involved for up to a decade.
Apple has several major efforts underway in health, ranging from its Apple Watch, which monitors heart health and movement, to its employee health clinics. It has hired dozens of doctors in a wide range of specialties, and has seen some high-profile departures, as it slowly moves into the $3.5 trillion medical sector. CEO Tim Cook has gone as far as to say that it could be the company’s “greatest contribution” to mankind.
As Cardiology Today previously reported at the meeting, the large-scale, app-based study enrolled 419,297 participants during an 8-month period, of whom 0.52% received an irregular pulse notification. Nearly half of participants (44%; n = 945) who received a notification went on to attend the first telehealth study visit. The ECG patch was mailed to 70% of participants (n = 658) and 68% returned their patch for analysis. Mean time to hookup was 13 days and mean wear time was 6.3 days. Of 450 participants who received an ECG patch to wear at home, 34.8% had observed atrial fibrillation (97.5% CI, 27-43).
“The absence of atrial fibrillation on a subsequent ECG patch does not imply that the initial notification was a false positive,” Marco Perez, MD, associate professor of medicine (cardiovascular medicine) at Stanford University Medical Center, and colleagues wrote. “Rather, atrial fibrillation may have been paroxysmal and infrequent, which is the most common pattern in early-stage atrial fibrillation. The index atrial fibrillation episode may have ended by the time the ECG patch was worn.”
Harvard T.H. Chan School of Public Health, Apple, and the National Institutes of Health today launched the Apple Women’s Health Study.
The large-scale longitudinal study, led by a team of researchers at Harvard Chan School, leverages participants’ voluntary use of a smartphone research app to advance understanding of menstrual and gynecological health.
By making use of information and study activities from personal devices, the first-of-its-kind study will shed light on women’s overall health needs across the lifespan. The multi-year study has the potential to become the largest and longest-running longitudinal study of women’s health in the U.S.
Spending for consumer digital healthcare companies is set to explode in the next few years; the Office of the National Coordinator for Health Information Technology is currently reviewing the requirements for data sharing with the Department of Health and Human Services, and their initiatives will unlock a wave of data access never before seen in the U.S. healthcare system.
Already, startups and large technology companies are jockeying for position over how to leverage this access and take advantage of new sensor technologies that provide unprecedented windows into patient health.
Venture capital investors are expected to invest roughly $50 billion in approximately 4,500 startups in the healthcare industry, according to data from CB Insights. In all, there have been 3,409 investments made in the healthcare market through the third quarter of 2019, with 31% of those deals done in what CB Insights identifies as digital health companies.
The University of Pennsylvania School of Engineering and Applied Science announced today the largest gift in the School’s history—a $25 million commitment from Harlan M. Stone, C’80, PAR’13, to support the construction of a new Data Science Building.
The building, which will be located at the corner of 34th and Chestnut Streets, will serve as a hub for cross-disciplinary collaborations that harness expertise, research, and data across Penn’s 12 schools and numerous academic centers. Upon completion, the Data Science Building will centralize resources that will advance the work of scholars across a wide variety of fields while making the tools and concepts of data analysis more accessible to the entire Penn community.
Traditional electronic engineering degrees should be reimagined to embrace AI and machine learning, according to a prominent UK academic.
Bashir Al-Hashimi, dean of engineering at Southampton University, proposes a new “engineering in the era of AI” degree.
Speaking at the recent TechWorks Summit, a gathering of representatives from the UK “deep tech” industries, Al-Hashimi said UK engineering departments are losing candidates to computer science. This is partially due to increased goverment investment in computing and coding instruction over the last five years. There has not been a similar investment in engineering subjects, he pointed out.
Princeton University, Center for Statistics and Machine Learning
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Nine data-driven research projects have won funding from Princeton University’s Schmidt DataX Fund, which aims to spread and deepen the use of artificial intelligence and machine learning across campus to accelerate discovery.
How did Black Lives Matter come into being? This movement changed how we push for racial justice, but surely it didn’t begin in 2012 when the hashtag was created. What’s the longer genealogy of black technology?
I recently had the pleasure of visiting Strand Books to hear Ruha Benjamin interview Charlton D. McIlwain about his new book Black Software. This post is a liveblog of that talk.
Deforestation of the Brazilian Amazon has hit the highest annual level in a decade, according to new government data which highlights the impact the president, Jair Bolsonaro, has made on the world’s biggest rainforest.
The new numbers, showing almost 10,000 sq kms were lost in the year to August, were released as emboldened farm owners scuffled with forest defenders in Altamira, the Amazonian city at the heart of the recent devastation.
Facebook AI research’s latest breakthrough in natural language understanding, called XLM-R, performs cross-language tasks with 100 different languages including Swahili and Urdu, but it’s also running up against the limits of existing computing power.
Pew Research Center; Brooke Auxier, Lee Rainie, Monica Anderson, Andrew Perrin, Madhu Kumar and Erica Turner
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Majorities think their personal data is less secure now, that data collection poses more risks than benefits, and believe it is not possible to go through daily life without being tracked
Some of you might know me from my R- and stats-inspired illustrations on twitter). I’m excited to share that, as of October 2019, I am an Artist-in-Residence with RStudio. My goal as an RStudio Artist-in-Residence is to create useful and engaging illustrations and designs that welcome users to explore, teach, and learn about new packages and functions in R. In this post, I’ll share what motivates me to create R-related artwork, and what I’ll be working on at RStudio.
“During my residency, I’ve discovered that many areas of neuroscience touch on questions of timing, decision making and deliberation — concepts most jazz musicians think about as we write music, practice with a band and perform,” Sung continued. “Learning that these concepts have biological bases has been mind-blowing. I was also elated to see how jazz, with its key elements of rhythm, improvisation, with its own unique language and vocabulary, is an ideal music form to complement studies of the brain.”
Sung will conclude her residency with a musical debut inspired by her experience: a collection of jazz compositions entitled “JazzPlasticity.”
One vision of it is the shiny new Stanford Hospital, which wheeled in its first patients on Sunday morning after $2 billion in spending and a decade in planning and construction. It counts 368 patient rooms, occupies the square footage of 14.3 football fields, and towers 180 feet over Silicon Valley.
The building is like a candy shop for a health-tech enthusiast: There’s a fleet of 23 self-driving robots, each about the size of a big office printer, designed to trek through the hallways at 2 miles an hour transporting heavy items like waste, linens, and gift store merchandise. There’s a food-truck-sized machine with 50,000 slots meant to dispense pills into single-dose packets. (It’s connected with distribution and electronic health records systems, a configuration being billed as first in the world.)
North Little Rock, AR “The sixth annual Arkansas Bioinformatics Consortium conference is set for Feb. 10-11 at the Wyndham Riverfront in North Little Rock. Its theme is ‘Artificial Intelligence in Arkansas.'”
Burbank, CA November 23, starting at 10 a.m. “At the end of 2019, let’s get together and have an entire day of R fun at Warner Bros in Burbank. 2019 has been a great year for SoCal R users. Several R Users Groups and R-Ladies either started or restarted to serve all communities in Southern California.” [free, registration required]
Caligari, Italy March 17, 2020, and IUI 2020 workshop. “This workshop aims to investigate how we can apply AI methods towards future AUIs. More specifically, using a hands-on approach, we will explore the application of AI and Machine Learning (ML) towards objectively improving aspects such as usability, reliability, and aesthetics while adapting UIs.” Deadline for submissions is December 20.
“Look forward to WSDM Cup 2020 tasks starting November 20th! WSDM Cup is a competition-style event co-located with the leading WSDM conference. This year, we have three exciting competition tasks from Microsoft Research, 4Paradigm and Sichuan Airlines, each of whom makes available 1 or more industrial scale datasets, enabling research on new problems.”
“The Data Science for Social Good Fellowship is a full-time summer program to train aspiring data scientists to work on machine learning, data science, and AI projects with social impact in a fair and equitable manner.” Deadline for applications is January 31, 2020.
“I’ve been leveraging the Featuretools library to significantly reduce my time spent building predictive models, and it’s unlocked a new class of problems that data scientists can address. Instead of building predictive models for single games and specific responses, we’re now building machine learning pipelines that can be applied to a broad set of problems. I presented an overview of our approach at the AI Expo in Santa Clara, and the slides from the talk are available here.”
I grew up in Wisconsin, and have lived in Iowa, Minnesota, and New York. Except for a two-year stint in the Bay Area, I’ve experienced winter — real winter, with lots of snow, below-freezing temperatures, and little daylight — every year of my life and never had a problem with it. So I was surprised when my last two Vermont winters put me on my ass. In winter 2017-18, I was depressed, anxious, wasn’t getting out of bed in the morning, spent endless time on my phone doing nothing, and had trouble focusing on my work. And I didn’t realize what it was until the first nice spring day came, 70 and sunny, and it hit me: “holy shit, I’ve been depressed because of winter” and felt wonderful for the next 5 months, like a completely different person. Then last year I was so anxious that it would happen again that all that stuff was worse and started basically a week into fall.
PyTorch has become one of the most popular deep learning frameworks in the market and certainly a favorite of the research community when comes to experimentation. As a reference, PyTorch citations in papers on ArXiv grew 194 percent in the first half of 2019 alone, as noted by O’Reilly. For years, Facebook has based its deep learning work in a combination of PyTorch and Caffe2 and has put a lot of resources to support the PyTorch stack and developer community. Yesterday, Facebook released the latest version of PyTorch which showcases some state-of-the-art deep learning capabilities.
Haskell has a proliferation of libraries to choose from for all of your basic backend needs, from logging to database access to routing and web server definition. It’s nice to have the freedom of choice, but if you’re just starting out, the amount of decisions needed can be overwhelming. Maybe you’re not even confident enough yet that you’ll be able to discern important differences between all the choices out there. You need to query your database. Do you want the strong column name guarantees and deep SQL embedding that Squeal gives you, or would you prefer the relative simplicity of Opaleye while still getting type safety? Or maybe it would be better to just use postgresql-simple and keep things really easy?