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Augmented reality system helps medical professionals

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The coming together of medics and technologists has shown how a mixed reality system can allow medical practitioners to view and effectively interact with virtual replicas of patients’ organs, bones and body parts.

The new technology comes from Birmingham City University’s Digital Media Technology Laboratory (DMT Lab). Although the system is still in development it has, as tests have shown, enabled medics to interact with virtual models of organs and bones. The interactive experience also changes models of patient data. This is achieved by the medic through the use of freehand movements.

This type of augmented reality technology could lead to new developments by medical software companies to assist medics in their pre-operative assessments (testing out medial procedures), as well as providing new learning models for medical students.

There are also hardware changes to come: augmented reality headsets, goggles, and contact lenses are the types of innovations that will let medical users project digital information over the real-life image they see. For example, drawing blood from the veins of a patient can be made easier with the help of vein scanners, designed to ease the process.

Importantly, with the Birmingham City technology, the augmented reality system also tells medics what might happen if procedure B is selected over procedure A; or if treatment 2 was used in place of treatment 1. This is made possible through the input of real patient medical records. The types of experiences are not only surgical; medics can also test out what might happen to patients long-term where harmful addictive substances are taken.

The basis of the system is advanced motion detecting sensors plus new developments with freehand interaction and the application of mixed reality software. The lead developer, Dr Ian Williams said to his university’s website: “We are developing this system as a platform to allow medical professionals to interact with genuine patient data and manipulate it by hand to educate and inform patients.”

The researcher adds: “The real advantages this brings are being able to visually demonstrate parts of the anatomy, using virtual models which can be customized for each patient and show how they have been impacted by lifestyle choices or how they may be changed following treatments or surgery.”

A possible further development with the system is with the creation of customized models that can be shared with the patient. This could, if felt appropriate, increase the engagement of patients’ with intended treatments and raise understanding. There may be some resistance from some in the medical field with the biggest obstacles relating to education, cultural change and acceptance.

These notwithstanding, augmented reality could become a driving force in the future of medicine.

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Canadian startup Deep Genomics uses AI to speed up drug discovery

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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.

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Health service partners with Alexa to provide medical support

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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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AI technology from IBM detects breast cancer risk before it happens

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IBM has taken a step forward in disease prevention by designing an artificial intelligence technology that can predict the risk of breast cancer developing up to one year before the first signs of cancer appear.

With this new step in medical diagnosis, IBM has developed an artificial intelligence model which is capable of predicting malignant breast cancer within a year with an 87 percent accuracy rate (when the output from the machine is compared with expert radiologists.) In addition, the technology could correctly predict 77 percent of non-cancerous cases.

The prediction methods uses both mammogram images and medical records in order to make the assessment, based on a data review of the medical evidence. This is the first application of AI to draw upon both images and data to make a prediction in relation to breast cancer.

At the heart of the deep neural network technology is an algorithm, which was trained by IBM technologists along with medical professionals from Israel’s largest healthcare organizations. The training of the artificial intelligence took place using anonymized mammography images which were linked to biomarkers (like patient reproductive history) together with clinical data. The training data-set consisted of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017.

The aim of the medtech is not to replace the physician, but to act as a ‘second pair of eyes’, providing a backup in the event that something has been missed through conventional patient assessment. This could prove especially useful in areas with staff shortages where a second medical professional is not available to provide a second assessment.

An assessment of the technology has been published in the journal Radiology. The research paper is titled “Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.”

In related news, IBM is applying artificial intelligence to catch Type 1 diabetes much earlier. IBM’s other health technology project could help identify patients at risk and help chart a course for tracking the condition. The predictive tool is a joint project between IBM and JDRF (formerly known as the Juvenile Diabetes Research Foundation).

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