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.”
North America’s first digital hospital launches second generation Command Centre
Do the words ‘command centre’ make you think of huge rooms with NASA scientists, expertly making sure a Mars rover lands safely on the Red Planet?
What if a command centre could revolutionize the patient experience in one of the busiest hospitals in North America, bringing a new standard of patient-centered, quality healthcare?
Combining Artificial Intelligence, Machine Learning, and professional expertise, Humber River Hospital in Toronto has launched the world’s first clinical analytic applications, in partnership with GE Healthcare Partners (GEHC).
Displayed on large-screen monitors at HRH’s 4,500 square-foot Command Centre, these four new applications or analytic ’tiles’ use “standardized early warning systems, predictive analytics, real-time information from multiple digital systems,” alongside the professional expertise of experienced nurses.
Canadian Patient Safety Institute and Canadian Institute for Health Information data shows that 1 in 18 hospital stays in Canada involved at least one harmful event. This addition to the Command Centre means quicker alerts for clinical staff, and better protection for patients with conditions that make them vulnerable to risks of adverse events, or adverse outcomes.
The Humber River Hospital is the Greater Toronto Area’s (GTA) largest acute care centre, serving a catchment area of more than 850,000 in the city’s northwest. Opening in 2015, it was also North America’s first fully digital hospital.
Just two years later, HRH opened the first generation of its Command Centre, a data-driven ‘mission control’ offering real-time insight on patient flow, via advanced algorithms and predictive analytics. As a result, the hospital has “unlocked” the equivalent of 35 additional beds — and the ability to treat thousands of additional patients.
Get an inside look at HRH’s Generation 2 Command Centre:
DX Journal covers the impact of digital transformation (DX) initiatives worldwide across multiple industries.
Canadian startup Deep Genomics uses AI to speed up drug discovery
One of the biggest challenges pharmaceutical companies face is with the time taken to discover new drugs, develop them and get them to market. This lengthy process is punctuated with false starts. Startup Deep Genomics uses AI to accelerate the process.
Canadian startup Deep Genomics has been using artificial intelligence as a mechanism to speed up the drug discovery process, combining digital simulation technology with biological science and automation. The company has built a platform which uses machine learning to delve into the molecular basis of genetic diseases. The platform can analyze potential candidate drugs and identify those which appear most promising for further development by scientists.
The drug development process is dependent upon many factors, such as those relating to combining molecules (noting the interactions between hundreds of biological entities) and with the assessment of biomedical data. The data review required at these stages is highly complex. For these reasons, many researchers are seeking algorithms to help to extract data for analysis.
According to MaRS, Deep Genomics is addressing the time consuming element involved in the initial stages of drug discovery. The artificial intelligence system that the company has designed is able to process 69 billion molecules, comparing each one against around one million cellular processes. This type of analysis would have taken a conventional computer (or a team of humans) many years to run the necessary computations.
Within a few months, Deep Genomics AI has narrowed down the billions of combination to shortlist of 1,000 potential drugs. This process is not only faster, it narrows down the number of experiments that would need to be run, saving on laboratory tests and ensuring that only those drugs with a high chance of success are progressed to the clinical trial stage.
This type of system goes some way to addressing the lengthy typical time to market, which stands at around 14 years for a candidate drug; as well as reducing the costs for drug development, which run into the billions of dollars per drug.
Health service partners with Alexa to provide medical support
The U.K. National Health Service (NHS) is to partner with Amazon’s Alexa in order to provide health information. This is being piloted as an alternative to medical advice helplines and to reduce the number of medical appointments.
While the U.K. NHS is much admired around the world as a free-at-the-point-of-use healthcare system, health officials are always keen to find ways to reduce the strain on the systems, especially relating to medical visits where the process of booking appointments and waiting times for sessions with doctors can be lengthy. The average time to obtain a non-medical emergency appointment with a general medical practitioner is averaging around two weeks.
Although a non-emergency medical helpline is active (accessed by dialling 111), plus an online system, health officials are keen to explore other ways by which the U.K. population can access medical services. For this reason, NHS England is partnering with Amazon.
The use of Alexa voice technology not only offers an alternative service for digitally-savvy patients, it provides a potentially easier route for elderly and visually impaired citizens, as well as those who cannot access the Internet through a keyboard, to gain access to health information. This fits in with a new initiative from the U.K. Government called NHSX, which is about the NHS Long Term Plan intended to make more NHS services available digitally.
As PharmaPhorum reports, Alexa can now answer questions such as “Alexa, how do I treat a migraine?” and “Alexa, what are the symptoms of flu?”
Outside of the U.K., Amazon is working with several healthcare providers, including digital health coaching companies, in order to launch six new Alexa healthcare ‘skills’. According to Rachel Jiang, head of Alexa Health & Wellness: “Every day developers are inventing with voice to build helpful and convenient experiences for their customers. These new skills are designed to help customers manage a variety of healthcare needs at home simply using voice – whether it’s booking a medical appointment, accessing hospital post-discharge instructions, checking on the status of a prescription delivery and more.”
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