Medical scientists and engineers have come together to develop an artificial intelligence system designed to detect often-missed cancer tumors, thereby helping to boost patient survival rates.
Researchers based at University of Central Florida developed the system by teaching a computer platform the optimal way to detect small specks of lung cancer in computerized tomography (CT) scans. These are of the type, according to size and appearance, that radiologists sometimes have difficultly in identifying.
In trials, the healthcare artificial intelligence system was found to be 95 percent accurate in total. Moreover, this was ahead of the typical scores achieved by human medics, which usually fall within the range of 65 percent accuracy.
The method used to train the artificial intelligence platform was not dissimilar to the way that facial-recognition software is taught key characteristics in relation to image analysis. To train the platform, the researchers provided in excess of 1,000 CT scans (taken from the U.S. National Institutes of Health database) to the software.
Over time the platform was taught to ignore other tissue, nerves and masses found in the CT scan images and instead to only focus on lung tissues and abnormal formations that could be tumors. The platform began to show success, and learnt to differentiate between cancerous and benign tumors. Given that successful diagnosis and treatment of lung cancer is highly dependent on early detection of lung nodules, developing a system to assist with this can help to boost patient survival rates.
Discussing how the platform was developed, researcher Rodney LaLonde explains: “We used the brain as a model to create our system…You know how connections between neurons in the brain strengthen during development and learn? We used that blueprint, if you will, to help our system understand how to look for patterns in the CT scans and teach itself how to find these tiny tumors.”
The new medical imaging research will be presented to MICCAI 2018 (21st International Conference on Medical Image Computing and Computer Assisted Intervention), which takes place in Granada, Spain during September 2018. The associated conference paper is titled “S4ND: Single-Shot Single-Scale Lung Nodule Detection.”
AI and ‘Heart-on-a-Chip’ — new weapons to combat heart disease
New technology has been developed in the fight against heart disease. This will be realized through a new partnership between two biotechnology companies: Insilico Medicine and Tara Biosystems.
Heart disease is the leading cause of death in many high-income countries. Heart disease describes a range of conditions that affect the heart, and it is interchangeable with cardiovascular disease. The types of diseases include blood vessel diseases, such as coronary artery disease; heart rhythm problems (arrhythmias); and heart defects people are born with (congenital heart defects), and others.
The new partnership is working on the notion that the old tools and traditional steps of cardiac disease research, described as a combination of Petri dishes and “hit-and-miss” drug discovery, are no longer suitable. In their place the researchers are working on artificial intelligence and drug testing with human tissue. This type of technology also avoids the need for animal research.
By functioning together, the artificial intelligence and so-called “Heart-on-a-chip” technology are set to help medical researchers discover drugs to fight heart disease faster and at a lower cost. This forms part of the advancements with ‘lab-on-a-chip’ technology, which describes is devices that integrate one or several laboratory functions on a single integrated circuit. These devices are typically only a few square millimeters in size, and they are used to achieve automation and high-throughput screening.
Insilico Medicine has been teaching its artificial intelligence system to predict the therapeutic use of new drugs before they enter the human testing process. Insilico’s Alex Zhavoronkov explains further: “We interrogate hundreds of disease-relevant assays on a regular basis to identify those biological systems that we can trust to validate the targets and molecules identified using our end-to-end drug discovery pipelines.”
Tara Biosystems, in a complimentary role, has grown actual human heart cells under laboratory conditions. This biological side of the partnership allows the cells to be tested with different drugs and monitored for side effects.
According to Tara’s Misti Ushio (quoted by Select Science): “At TARA, we engineer human cardiac tissue to mimic specific human disease phenotypes which are used to validate novel targets and rapidly evaluate new compounds for positive effects on cardiac function. Partnering with Insilico Medicine further maximizes TARA’s cardiac drug discovery platform.”
The two biotechnology companies, working together, aim to discover new treatments for heart disease. This will have the societal benefit of saving lives and extending the human lifespans.
A road map for assessing blockchain health care startups
Blockchain-backed health care startups are all the rage right now, and a new open-source tool that tracks data about startups in the aim to help potential investors navigate the pile of startups clamouring for their time and money.
“Blockchain” truly is the buzzword of 2018. In February this year Reuters reported that companies who added “blockchain” to their name experienced a temporary boost in share price, and it’s being applied to health care in a very big way.
Outlets credit blockchain startups with creating new opportunities for health care, and blockchain is being seen, overwhelmingly, as a transformative technology for the health care industry, and even changing the world for the better. In the midst of all this, as in any industry utilizing emerging technologies, there’s concern that not all the blockchain-backed startups are living up to the hype they create around themselves.
Digital biomarker registry Elektra Labs and the Center for Biomedical Blockchain Research at the Icahn School of Medicine at Mount Sinai have partnered to create a open-source database of blockchain health care startups that have passed their review.
Are you thinking about investing in a healthcare blockchain… but are unsure what’s hype vs legit? 🏥💸
— Andy Coravos (@AndreaCoravos) July 25, 2018
Andy Coravos, the CEO of Elektra Labs, and Noah Zimmerman, the Director of Health Data and Design Innovation Center at Icahn School of Medicine at Mount Sinai, wrote a piece about the project in the health and medicine news website Stat about the “most promising blockchain projects in the health care ecosystem” and how buyers and investors should be aware of startups that could be taking them for a ride.
“After reviewing more than 150 white papers, one thing is clear: many of these blockchain projects fall somewhere between half-baked and overly optimistic, with strong marketing teams and shaky technical fortitude (we excluded the outright scams, and strove to be generous to the remaining early projects),” reads the Stat piece by Coravos and Zimmerman.
The researchers on this project established a set of criteria and questions that they used to establish if a blockchain project is “quality,” as they put it. Some of these questions include: “Does the project have a technical white paper that outlines the project roadmap?”, “Does the project have a demo or working project?” and “Does the project publish a public code base?”
Other metrics that are tracked include funding and how funding is raised.
“Health care blockchains have raised hundreds of millions of dollars of capital which will be deployed in the next few months or years,” reads the Stat piece. “(A)nd these projects will form the foundation of our healthcare system for years to come.”
How digital collaboration lets humans be human
By: Sowri Krishnan
Many of us have grown up on a healthy diet of R2-D2, Skynet, Autobots, JARVIS and the Matrix. What was a mere notion – artificial intelligence, bots and algorithms coexisting with and influencing our lives – has now become integral to what we do, both personally and professionally. AI is disrupting the very core of how we interact, both with our fellow humans and with technology.
The impact on our professional lives is particularly significant. Advancements in digital technology are no longer just about bottom-line improvements or creating the next Uber; they’re about identifying ways to enhance our uniquely human capabilities through digital enablement. The result: more meaningful interactions and transactions in our work lives.
By collaborating with the new machines, we can become better at “being human” in how we perform our work, whether we’re caregivers, lawyers, bankers or customer service reps. When we let digital technologies do what they do best – and enable humans to focus on what they do best – we can impact the business much more dramatically than either could accomplish on its own.
Collaborating Where It Counts
We’re seeing this at Narayana Health, an India-based hospital network that we’re partnering with to improve its post-operative care for patients in the intensive care unit (ICU).
In a typical ICU, medical practitioners and caregivers endeavor to administer precise, rapid care, even while they rely on heavily manual documentation processes. Everything from patient progress and vital stats, to lab work and medication dosages is recorded and stored on reams of paper. Even small margins of human error could negatively impact the quality of patient care and outcomes, such as delayed diagnosis, medication errors and faulty patient histories. In the U.S. alone, medical error is the third-leading cause of death, after heart disease and cancer.
Narayana Health sought to enable nursing staff to focus on the work of caregiving by applying digital to process efficiencies and elimination of human error in the ICU. The goal: improve outcomes even while treating more patients by freeing up the resources needed to provide care.
A Human-Centered Approach
Just as we aimed to use digital technology to emphasize the human capabilities of Narayana’s medical staff, we also took a human-centered approach to formulating a solution:
- We embedded a research team into Narayana’s ICU in Bangalore for six months to observe daily interactions among caregivers and patients.
- Our team then determined how staffing levels, time of day, severity of cases and patient load affected the ability to effectively manage patient care.
- We produced multiple prototypes, directly on an iPad, at the point of care, to elicit feedback from the ICU staff.
- We conducted several studies to identify different caregiver personas, in terms of their interaction with patients, hospital devices and systems.
Using this human-centered approach, we developed a technical architecture to standardize, digitize and automate clinical processes. The solution integrated the ICU ecosystem of data sources, including information from medical devices and existing hospital systems. It also enabled tailored alerts and indicators related to patient state. Because the system could churn through data much more quickly and effectively, it reduced dependence on the vigilance of medical staff, who could focus on patient care.
The Benefits of Collaboration
The project generated two simultaneous benefits:
- First, it brought a degree of automation at the point-of-care, resulting in greater operational efficiencies for nurses.
- Second, it introduced standardization through protocol-driven care. This reduced the need for human oversight over standard processes by 80%, and increased nursing efficiency by 45%. Nurses were freed to provide better care to patients, and ICU stays were reduced by 15%.
At the end of the day, it’s exciting to watch the developing capabilities of digital technologies. However, it’s far more rewarding to see what humans and the new machines can accomplish when they work together.
This article originally appeared on the Digitally Cognizant Blog
Cognizant (Nasdaq: CTSH) is dedicated to helping the world’s leading companies build stronger businesses — helping them go from doing digital to being digital.
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