4 Ways IBM Watson's Artificial Intelligence Is Changing Healthcare


Some say that artificial intelligence (AI) will radically change healthcare in the future. But that prediction overlooks an important detail: AI is already significantly changing healthcare. IBM (NYSE:IBM) Watson Health general manager Deborah DiSanzo spoke at the annual J. P. Morgan Healthcare Conference on Wednesday. She provided an update on the progress that IBM Watson, the AI system famous for beating Jeopardy! DiSanzo highlighted four areas where AI is making a big difference today.

Why 500 million people in China are talking to this AI


When Gang Xu, a 46-year-old Beijing resident, needs to communicate with his Canadian tenant about rent payments or electricity bills, he opens an app called iFlytek Input in his smartphone and taps an icon that looks like a microphone, and then begins talking. The software turns his Chinese verbal messages into English text messages, and sends them to the Canadian tenant. In China, over 500 million people use iFlytek Input to overcome obstacles in communication such as the one Xu faces. Some also use it to send text messages through voice commands while driving, or to communicate with a speaker of another Chinese dialect. The app was developed by iFlytek, a Chinese AI company that applies deep learning in a range of fields such as speech recognition, natural-language processing, machine translation, and data mining (see "50 Smartest Companies 2017").

Leverage AI to revolutionize and advance healthcare


What is Intel doing in the area of artificial intelligence/machine learning? Artificial intelligence is causing a technological revolution. Intel recognizes the power AI has to transform society and industries. We are committed to democratizing AI and machine-learning innovations so that everyone has the opportunity to benefit. To that end, we've been doing a number of things: This group focuses on solutions that make it easy to incorporate custom AI solutions into existing infrastructure.

Fight Against Cancer with Artificial Intelligence and Big Data - OpenMind


From anywhere and with just a mobile phone, anyone can become an air traffic controller, or at least a virtual air traffic controller. One can follow the world traffic flow of airplanes live and find out where an aircraft is coming from and where it is headed. One just has to take advantage of the millions of pieces of data that fly across the Internet. This is the magic power of Big Data. Artificial intelligence then enters the picture to find patterns and give meaning to the massive and heterogeneous information stream.

AI could have 'immense' benefits for NHS, says tech committee chair


The chairman of the Commons Science and Technology Committee has thrown his weight behind recommendations for the widespread introduction of artificial intelligence (AI) to the NHS. Norman Lamb said the rewards could be "immense" in terms of cost savings and diagnosing patients more quickly. But he warned people's privacy must be protected and that the health service should get a "fair deal" from technology companies implementing the systems. The report, by the Reform think tank, said AI could be used to target treatment by predicting which individuals or groups might be at risk of illness, to send patients to the most appropriate services or to enable them to "self-care". The technology can also be used to improve diagnoses, Reform said, including for breast cancer – 30 times faster and more accurately than humans, the group claimed.

The case against deep-learning hype


Three big pharmaceutical firms--Pfizer, Amgen, and Sanofi--are working together to use blockchains to speed up clinical tests of new drugs, according to CoinDesk. The problem: Patient data that's crucial to locating individuals for clinical trials is usually scattered across multiple proprietary systems that are often incompatible with each other. That can make it hard to recruit for trials. How blockchains could help: A distributed ledger could allow individual patients to store data anonymously and make it visible to trial recruiters, who could then reach out to individuals who meet the eligibility criteria for a given trial. It could also streamline communication between doctors and patients during the trial.

30 innovations that improved the world in 2017


From global health to social justice to humanitarian aid, a slew of scientists, technologists, and activists came together this year to create impactful solutions to some of our most pressing problems. SEE ALSO: 9 incredible ways we're using drones for social good In no particular order, here are 30 innovations that made a tangible difference in 2017. This paper device, which only costs 20 cents to make, can help scientists and doctors diagnose diseases like malaria and HIV within minutes -- no electricity required. The Paperfuge, developed by Stanford assistant professor of bioengineering Manu Prakash, is a hand-powered centrifuge that was inspired by a whirligig toy. It can hold blood samples on a disc, and by pulling the strings back and forth, it spins the samples at extremely fast rates to separate blood from plasma, preparing them for disease testing.

Cancer: A Computational Disease That AI Can Cure

AI Magazine

From an AI perspective, finding effective treatments for cancer is a high-dimensional search problem characterized by many molecularly distinct cancer subtypes, many potential targets and drug combinations, and a dearth of highquality data to connect molecular subtypes and treatments to responses. The broadening availability of molecular diagnostics and electronic medical records presents both opportunities and challenges to apply AI techniques to personalize and improve cancer treatment. We discuss these in the context of Cancer Commons, a "rapid learning" community where patients, physicians, and researchers collect and analyze the molecular and clinical data from every cancer patient and use these results to individualize therapies. Research opportunities include adaptively planning and executing individual treatment experiments across the whole patient population, inferring the causal mechanisms of tumors, predicting drug response in individuals, and generalizing these findings to new cases. The goal is to treat each patient in accord with the best available knowledge and to continually update that knowledge to benefit subsequent patients.

For Artificial Intelligence, the Future Is Now


Watershed technologies like AlphaGo make it easy to forget that artificial intelligence (AI) isn't just a futuristic dream. It's already here -- and we interact with it every day. Sensing traffic lights, fraud detection, mobile bank deposits, and, of course, internet search -- each of these technologies involves AI of some kind. As we have grown used to AI in these instances, it has become part of the scenery -- we see it, but we no longer notice it. Expect that trend to continue: As AI grows increasingly ubiquitous, it'll become increasingly invisible.

Knowledge Discovery in Databases: An Overview

AI Magazine

William J. Frawley, Gregory Piatetsky-Shapiro, and Christopher J. Matheus After a decade of fundamental interdisciplinary research in machine learning, the spadework in this field has been done; the 1990s should see the widespread exploitation of knowledge discovery as an aid to assembling knowledge bases. The contributors to the AAAI Press book Knowledge Discovery in Databases were excited at the potential benefits of this research. The editors hope that some of this excitement will communicate itself to AI Magazine readers of this article. Computers have promised us a fountain of wisdom but delivered a flood of data. The size and number of databases probably increases even faster.