Deficiency of access to health information said to restrict potential of machine learning technology

As machine learning technology sustains to advance at a rapid pace, providers are excited by the potential of this kind of artificial intelligence to predict which sufferers are most at risk for clinical events that need early intervention.

Although, these medical breakthroughs are being hampered by the deficiency of health data necessary to learn the complex patterns needed to positively affect patient care.

That is the consensus of healthcare stakeholders who gathered at Wednesday’s Machine Learning in Healthcare: Industry Applications conference in the Boston to discuss the technology’s promise and challenges.

Research released earlier this month by MarketsandMarkets projected that the healthcare artificial intelligence market is hoped to grow from $667.1 million in the year of 2016 to more than $7.9 billion by the year of 2022, a compound yearly growth rate of 53% over the forecast period. Machine learning technology is accelerating at a rate beyond Moore’s Law, with algorithms and models doubling in capability every 6 months.

Among the potential applications: medical imaging, drug discovery, diagnostics, precision medicine, as well as patient information and risk analysis. In fact, a study presented this week at the American Thoracic Society International Conference in Washington demonstrated that a machine-learning algorithm has the capability to recognize hospitalized patients at risk for severe sepsis and septic shock using information from electronic health records (EHRs).

In accordance to Russ Wilcox, partner of venture capital firm Pillar, machine learning technology is presently benefitting from a “trifecta” of technology trends—big data (a flood of digital information that doubles every 3 years), better hardware (optimized processors and storage) and smarter algorithms.

“90% of the world’s digital information is less than 2 years old, and (that trend) is accelerating even faster,” Wilcox told the Machine Learning conference.

Yet, in healthcare, he lamented the fact that much of the information is trapped in silos, which is stifling machine learning’s promising applications in medicine.

“So several of the other industries are way ahead of us in terms of considering about how to bring automation and digital tools to personalize our access” to data, stated John Brownstein, chief innovation officer at Boston Children’s Hospital, who summed up the issue in healthcare as being a deficiency of data accessibility and quality.

On the flip side, Brownstein pointed out that the large consumer technology companies have access to good quality information that enables automation and machine learning, resulting in a high level of personalization.

In the public sector, AI isn’t on the agenda of the Centers for Medicare and Medicare Services (CMS), even though the agency has increasingly been issuing updated healthcare data to improve transparency in the Medicare program and to provide more timely data for providers, researchers and beneficiaries, claims Niall Brennan, former chief data officer at CMS.

“While we did a ton of data work and re-centered and reengineered CMS as a more data-driven organization, I am afraid AI is so far off its radar screen that if you said AI to somebody at CMS they might consider you were talking about Allen Iverson,” said Brennan.

CMS is the greatest single U.S. health payer, generating enormous amounts of data. Although, as Brennan pointed out, it is primarily claims data, with the agency “missing nearly all of the clinical and genomic data.” Even so, he believes AI and machine learning technology could give CMS the capabilities to utilize data in new and creative ways and to generate actionable insights, he said.

Over the next 5 years, Brennan asserts that one of the key issues related to whether or not artificial intelligence and machine learning technology gain traction with huge public payers is “translating it into something tangible that will resonate with payers and lead them to consider them about realigning financial incentives” to make better the patient outcomes and reduce healthcare costs.

On the provider side, he made the case that the single most important driver for spurring the adoption of AI and machine learning technology is the transition from fee-for-service to value-based care “because it develops incredible incentives for providers to innovate and attempt to provide better care at lower costs.” At the similar time, Brennan cautioned against the hazards of “bolting innovative solutions on to a fee-for-service chassis.”

 

Apple Inc. plans to Bring Artificial Intelligence into Chips

Apple Inc. got an early beginning in artificial intelligence (AI) software with the 2011 introduction of Siri, a tool that lets users operate their smartphones with voice commands.

Now the electronics giant is bringing AI to chips.

Apple Inc. is working on a processor devoted particularly to AI-related tasks, in accordance with a person familiar with the matter. The chip, termed internally as the Apple Neural Engine, would make better the way the company’s devices handle tasks that would otherwise require human intelligence -- like facial recognition and speech recognition, claimed the person, who requested anonymity discussing a product that has not been made public. Apple Inc. refused to comment.

Engineers at Apple Inc. are racing to catch their peers at Amazon.com Inc. and Alphabet Inc. in the booming field of AI. While Siri gave Apple an early advantage in voice-recognition, competitors have since been more aggressive in deploying AI across their product lines, involving Amazon’s Echo and Google’s Home digital assistants. An AI-enabled processor would assist Cupertino, California-based Apple integrate more advanced capabilities into devices, specifically cars that drive themselves and gadgets that run augmented reality, the technology that superimposes graphics and other information onto a person’s view of the world.

“Two of the places that Apple is betting its future on require AI," claimed Gene Munster, former Apple analyst and co-founder of venture capital firm Loup Ventures. “At the core of augmented reality and self-driving cars is artificial intelligence.”

Improved Performance Apple devices presently manage complex artificial intelligence processes with 2 different chips: the main processor and the graphics chip. The new chip would let Apple offload those tasks onto a dedicated module designed particularly for demanding artificial intelligence processing, permitting Apple Inc. to improve battery performance.

Should Apple Inc. bring the chip out of testing and development, it would follow other semiconductor makers that have already launched dedicated AI chips. Qualcomm Inc.’s latest Snapdragon chip for smartphones has a module for handling artificial intelligence tasks, while Google declared its first chip, called the Tensor Processing Unit (TPU), in the year of 2016. That chip worked in Google’s data centers to power search results and image-recognition. At its I/O conference this year, Google declared a new version that will be available to clients of its cloud business. Nvidia Corp. also sells a similar chip to cloud customers.

The Apple AI chip is developed to make primary improvements to Apple’s hardware over time, and the company plans to instantly integrate the chip into many of its devices, involving the iPhone and iPad, in accordance to the person with knowledge of the matter. Apple has tested prototypes of future iPhones with the chip, the person said, adding that it is unclear if the component will be ready this year.

Apple’s operating systems and software features would integrate with devices that involve the chip. For instance, Apple has considered offloading facial recognition in the photos application, few parts of speech recognition, and the iPhone’s predictive keyboard to the chip, the person said. Apple also plans to offer developer access to the chip so third-party apps can also offload artificial intelligence-related tasks, the person stated.

Developer Conference Apple might select to discuss few of its latest advancements in AI at its annual developer’s conference in June. At the similar conference, Apple plans to launch iOS 11, its new operating system for iPhones and iPads, with an updated user-interface, individuals with knowledge of the matter said last month. The company is also said to discuss updated laptops with faster chips from Intel Corp.

An AI chip would join a growing list of processors that Apple has developed in-house. The company started designing its own main processors for the iPhone and iPad in the year of 2010 with the A4 chip. It has since issued dedicated processors to power the Apple Watch, the motion sensors across its products, the wireless components inside of its AirPods, and the fingerprint scanner in the MacBook Pro. The company has also tested a chip to run the low-power mode on Mac laptops.

In the year of 2015, Bloomberg reported that Apple’s culture of secrecy stymied the iPhone maker’s capability to attract top AI research talent. Since then, Apple has received multiple companies with deep ties to AI, has started issuing papers related to AI research, has joined a key research group and has made hires from the field. In the year of October 2016, Apple hired Russ Salakhutdinov from Carnegie Mellon University as its director of AI research.

 

Partners HealthCare & GE Healthcare merges for AI projects

Artificial intelligence (AI) is hoped to play an increasing role in healthcare delivery, but moving the application of predictive technology from the theory to reality has been a stumbling block. A latest partnership between Partners HealthCare and GE Healthcare is targeting at bridging this gap and bringing deep learning technology across the whole continuum of care.

Under a recently declared ten-year agreement between the Boston-based integrated delivery system and the health technology vendor, the partners expect to find ways to develop “new business models for applying AI to healthcare and establish products for extra medical specialties,” the announcement noted.

For instance, AI could be directed to solve issues in molecular pathology, genomics and population health.

The collaboration will occur through the newly developed Center for Clinical Data Science, a newly formed project of Massachusetts General Hospital and Brigham and Women’s Hospital.

The project will utilize multidisciplinary teams with broad access to data, computational infrastructure and clinical expertise. The initial concentration of the relationship will be on the development of applications that are intended to make better the clinician productivity and patient outcomes in diagnostic imaging.

“This is a significant moment for medicine,” stated David Torchiana, MD, CEO of Partners HealthCare. “Clinicians are inundated with data, and the patient experience suffers from inefficiencies in the healthcare industry. By merging the expertise at Mass General and Brigham and Women’s with the spirit of innovation at GE, this partnership has the resources and vision to increase the development and adoption of deep learning technology. Together, we can boost clinicians with the tools required to store, analyze and leverage the flood of information to more effectively deliver care to sufferers.”

Furthermore, the teams will co-develop an open platform on which Partners HealthCare, GE Healthcare and third-party developers can rapidly prototype, validate and share the applications with hospitals and clinics around the world.

 

Artificial Intelligence seen as Third Great Revolution bringing services to the masses

Artificial intelligence (AI) is being explained as the third great revolution in the field of business, following the Industrial Revolution and the Information Revolution. And if few industry observers are correct, it’ll have a transformative impacts on consumers, business and government markets around the globe.

In accordance to the report “Bot.Me: A revolutionary partnership: How AI is pushing man and machine closer together” from PwC, “AI has the possibility to become the great equalizer. Access to services that were conventionally reserved for a privileged few can be extended to the masses.”

The effects of that on business can’t be understated, as artificial intelligence has the possibility to open up major new markets or expand on existing markets. That means agencies that embrace artificial intelligence will have distinct competitive advantage, the study points out.

“As humans, there is a lot we are not good at,” claims AI developer Kaza Razat, quoted in the PwC study. “When we are making machines that are better at certain things than we are, it is still an extension of us. From an evolution standpoint, there are places where we have reached the end of our capacity.”

Still, artificial intelligence (AI) is merely as good as the data it uses the research stresses. That places greater emphasis on problems related to data quality and data governance.

Where artificial intelligence is hoped to have particularly dramatic impact is in areas around cybersecurity, privacy, cancer research and the treatment of other diseases, the study claims.

“With the huge amount of DNA data being recorded today, AI could revolutionize personalized healthcare by observing that data; wearables and ingestibles could monitor and correct human behavior to maximize life expectancy and increase wellbeing. We are already seen AI victoriously recognize autism in babies with 81% accuracy, and skin cancer with 91% accuracy.”

The study polled almost 2,500 consumers and business leaders on where they considered AI will have the most immediate impact. Their responses:

• 66% said treating cancer and other diseases


• 68% said cybersecurity and privacy


• 61% said personal financial security and fraud protection


• 62% said clean energy


• 58% said global education


• 56% said economic growth


• 56% said global health and well-being


• 50% said climate change


• 38% said income inequality


• 31% said gender inequality

More than 40% of consumers “believe AI will expand access to medical, financial, legal and transportation services to those with lower incomes,” the study claims.

 

Many patients keenly use mobile device to send info to providers

Despite uncertainties over the potential risk to data security and privacy, customers are becoming more comfortable with the idea to keenly use mobile device for managing their health.

In accordance to an online survey of 2,000 U.S. adults, taken by communications firm Ketchum, almost six in ten Americans with a smartphone claimed that they have shared information with a medical expert through a smartphone, mobile app or wearable device.

Moreover, about half of those surveyed demonstrated that they have an app that detects fitness, working out, health or medicine, while one in 4 respondents claimed that they’ve emailed or texted a photo of a medical problem to their doctor.

 “Devices for healthcare management are increasing, and individuals are using them in new and complex ways,” claims Valerie Delva, health strategy director at Ketchum North America. “Though present attitudes toward utilizing mobile technologies for health at the individual level are quite complicated, the insights here also speak to broader trends in the health ecosystem and the potential for these technologies to assist to make better the health results.”

At the similar time, about half of Americans stated that they have a lot to learn about how to use mobile device or health technology so that they can take advantage from them. Almost one in four admit that health and fitness tracking applications have made them feel bad, and more than one in 5 of those surveyed have stopped utilizing certain applications.

And, however the majority of respondents demonstrated they have keenly use mobile device or technology to interact with a medical expert, almost two in three stated that they yet prefer face-to-face interaction with their healthcare providers.

“Even though individuals are interested and need to use mobile device or technology to interact with their healthcare providers, there is also still a powerful population that does value face-to-face interaction, and I do not think that the two are mutually exclusive,” claims Delva.

Lisa Sullivan, executive vice president and North American technology practice leader at Ketchum, recommends that one of the most astonishing findings of the survey was that two in five Americans stated that they are comfortable using artificial intelligence.

About a third of respondents showed that they are likely to utilize an AI search tool like Siri, and 31% said they would be open to an AI health tracker. Although, Americans are not amenable to the concept of using an AI medical adviser (18%) or an artificially intelligent therapist (9%).

How can thorough learning affect healthcare?

Resorting to AI may sound like something from science fiction, but computer programs with superhuman capabilities have become reality with Google DeepMind’s recent vicory in beating an expert player at the game of Go.

Professor Neil Lawrence, University of Sheffield, although, is disappointed it took so long for thorough learning to crack the game of Go, particularly when computer programs were capable to beat humans at Chess over 20 years ago. Lawrence elaborated the data delusion and the present inefficiencies of deep learning in terms of the tools utilized.

“The tools you utilize should not limit the way you consider”, although, was the key principle of Diogo Moitinho de Almeida, Senior Data Scientist, Enlitic, who considers we can do better and that “deep learning is awesome.”

Some of the applications of deep learning at the Summit certainly did appear awesome. Ali Parsa, CEO of Babylon Health demoed their upcoming app which inquired the user a series of queries in case to determine the severity of the user’s medical symptom, in the similar way as a triage nurse. Parsa expects that deep learning can even take us one step further from sickcare to healthcare.

The move towards a more predictive instead than reactive healthcare system was also discussed during a panel on how AI will assist to enhance and personalize healthcare. Cosimo Gretton, a doctor at Guy’s and St Thomas’ NHS Foundation Trust elaborated how predictive analytics in healthcare is a transformative approach but it will need changes to the system so that clinicians can use the algorithms successfully.

Value Based Healthcare Transition Spurs Innovative Chances for Industry People

With Artificial Intelligence (AI) enabling a huge array of applications, healthcare agencies have been eager to layer their existing lines of business with AI-based facilities. While pharma agencies have been searching tools for tracking the effectiveness of therapeutics, imaging agencies have been augmenting the interpretability of scans through cognitive pattern interpretation.

Latest analysis from Frost & Sullivan, 2016 Global Outlook for the Healthcare Industry seeks the industry was worth $1.58 billion in the year 2015 and estimates this to reach $1.68 billion in the year 2016, progressing at a rate of 6.9%.

Nearly 24% of users presently use mobile apps to track health and wellness, 16% use wearable sensors and 29% use electronic personal health records. Primarily, 47% of users reported they would think about using wearables in the near future, prompting technology developers to design wearables with advanced sensing, capture and analytical functionalities. The gathered data from wearables are gaining relevancy through AI facilitated patient guidance and coaching.

Meanwhile, the healthcare agency has become more consumer-oriented and transparent with rating networks, incentives, penalties as well as online reviews for contributors and physicians.