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"How can AI transform the healthcare sector, in UAE???????????????????????????????????
16 February 2018

Healthcare
Insight
Technology

AI has led to drastic changes across sectors. In the healthcare sector, medical advances include breakthrough technologies such as:

- 3D printing to create human body parts, reproduce blood vessels and form skin cells
- Artificial eyes that enable patients to regain vision
- Implanted remote controlled devices that send electrical pulses to reduce the impact of headaches
- Artificial pancreas that measure blood glucose using a sensor and deliver appropriate amounts of insulin


On one hand, WHO has reported that the prevalence of chronic disease is expected to rise by 57% by 2020. On the other hand, advancements in detecting and diagnosing diseases are expected to minimize the cost of treating chronic diseases. These innovative technologies include genomics, proteomics, cell biology, stem cell and organ therapy, and minimally invasive and robotic surgery. Most importantly, majority of these new advancements are likely to be fuelled by Artificial Intelligence (AI).


AI in the global healthcare market

AI is revolutionizing the healthcare industry at lightning speed. Previously, technology in healthcare was limited to algorithms and tools to assist humans. Now, however, AI can augment human activity. From imaging to diagnosis, AI is able to do it all. Although this provides a wealth of opportunities, AI advancements require large investments. Research by Accenture does, however, suggest that the latter will generate annual savings of $150 billion for the US healthcare industry by 2026.





As per a 2016 study by Frost & Sullivan, the market for AI in healthcare is projected to reach $6.6 billion by 2021, representing a 40% compound annual growth rate. The report goes on to say that clinical support from AI will strengthen medical imaging diagnosis processes and using AI solutions for hospital workflows will enhance patient care delivery. Frost & Sullivan also reports that AI has the potential to improve outcomes by 30 to 40 percent while reducing treatment costs by as much as 50%. In addition, PwC research has estimated savings of up to 172 billion euros over the next 10 years in prevention of childhood obesity, diagnosis of dementia and diagnosis and treatment of breast cancer through AI adoption in the healthcare sector.







The rapid growth of healthcare AI is apparent when comparing investment in the industry over the years. In 2011, less than 10 healthcare start-ups received major investment. In 2016, this number rose to almost 70. The latter comes as no surprise as CB Insights regards healthcare as the most popular area of investment within AI. The figures are likely to increase as the industry continues to grow with the help of research and innovation.





Adoption of AI in UAE’s healthcare sector

UAE stands at the forefront of AI ahttp://valustrat.com/wp-content/uploads/AI-Healthcare-05-768x608.pngdoption and is an avid believer in AI-based economy. The country recently launched their first AI strategy termed “UAE Artificial Intelligence Strategy 2031” – the first of its kind in the region. The strategy aims to bring AI tools and technology to various sectors including healthcare. The official website mentions that AI will be used to minimise chronic and dangerous diseases.

PwC research suggests that two-thirds of the Middle East would be open to the idea of replacing human doctors with AI. The report also states that an insufficient workforce and a young population make the Middle East the ideal region for AI and robotics.





Keeping in line with the UAE’s AI strategy, Dubai Health Authority (DHA) is expected to launch the first radiology AI algorithm as part of Dubai Health Strategy 2021. The initiative will expedite the processing time for chest x-ray scans which are required for those seeking residency in the country.

AI will REdefine healthcare

As the healthcare industry undergoes a metamorphosis, there are several ways in which AI can be incorporated:

1) Robotic surgery

Robot-assisted surgery offers the greatest value potential in AI-based healthcare. Cognitive robotics can integrate information from pre-op medical records with real-time operating metrics to physically guide and enhance the physician’s instrument precision. The technology creates a database of surgical data and improves techniques, allowing it to improve outcomes. Machine learning will continue to improve results over time.

Mazor Robotics, based in the US, uses Artificial Intelligence to aid both minimally invasive surgical operations and complex surgery. Using their technology, a patient’s CT scan is uploaded onto a 3D computerized planning system to indicate where a surgeon should place implants—all before the patient even arrives. Mazor’s spinal surgery robot arm guides an orthopaedic surgeon’s instruments, allowing high precision.

2) Disease identification

Medical Artificial Intelligence breakthroughs have led to improved accuracy in the early detection of life-threatening diseases such as cancer. The American Cancer Society reports that 12.1 million mammograms are performed annually in the US, but a large percentage of these mammograms produce false results, with 20 percent of healthy women being told they have cancer. AI enables the review and translation of mammograms 30 times faster with 99% accuracy, making the procedure more reliable. Furthermore, AI powered consumer wearables and other medical devices are also being applied to oversee early-stage heart disease, enabling doctors and other caregivers to better monitor and detect potentially life-threatening illnesses at earlier stages. CardioDiagnostics has developed a device that is able to remotely monitor heart irregularities of the wearer and is used to improve cardiac monitoring and rhythm management.

Artificial Intelligence is also identified as a huge priority for tech giant Intel, as the company is active in many areas as of healthcare ranging from predictive clinical analytics to imaging Intel helped Sharp HealthCare in San Diego build a predictive model with 80 percent predictability of patient decline within an hour of an event happening. This advance notice enables strategically placed medical emergency teams to be located at key areas in hospitals in order to intervene before an event becomes life-threatening.

3) AI chatbot

Hospitals and clinics require a great deal of resources to manage patient inquiries via phone, e-mail, or live chat. However, automated AI chatbots can enable these organizations to save money and improve efficiency. Research suggests that by 2022, chatbots could save organizations $8 billion per year globally.





In April 2017, UK-based company Babylon Health raised close to $60 million. The company developed an app that assesses health with the help of an AI chatbot on your smartphone, after which it arranges virtual consultations with doctors if necessary. Around the same time, Berlin-based digital health startup Ada announced its entrance into the AI chatbot space.

AI chatbots in healthcare have been helping consumers select a benefit plan, providing customer service responses, helping triage symptoms, and guiding consumers to resources.

4) Data analytics powered decisions

A study by TechEmergence found that over 50% of respondents believe that “AI will be ubiquitous in healthcare by 2025.” The latter seems logical, considering that the healthcare industry collects vast amount of data which is challenging for physicians to assess. AI, however, can analyse large amounts of data efficiently using advanced algorithms to suggest treatment options. The more data points the technology has to work with, such as patient history, past treatment options, and available medications, the better conclusions it can make.

Google has launched an initiative called DeepMind Health, which creates partnerships between doctors, researchers and patients to identify and solve real healthcare problems. The technology utilises machine learning and systems neuroscience to build algorithms capable of mimicking the human brain. Data Diagnostics’ Quanum solution is another example that aims to assist decision making through AI-driven data analytics. Their objective is to help healthcare professionals achieve better clinical and financial outcomes, by providing the right data at the right point (point of care). Their system crawl data, analyses and projects outcomes that helps professionals identify gaps in quality, optimize test utilization, and help prevent patients’ conditions from worsening. Similarly, Microsoft is working on InnerEye – AI-powered computer vision designed to dramatically improve the productivity of radiologists.

5) Efficiency in drug research

The right medication makes a lot of difference for curing a disease, be it a viral infection or a chronic disease – the road to recovery is not as long as the road to discover the right medication. According to the

Drug research and discovery is a recent yet important application of AI in the healthcare sector. Directing the latest advances in Artificial Intelligence to streamline the drug discovery and drug repurposing processes possesses the ability to reduce both the time to market for new drugs and their costs. Pharma.AI, the Pharmaceutical Artificial Intelligence division of bioinformatics company Insilico Medicine, used AI was u to scan existing medicines that could be redesigned to fight Ebola. In one day, the program found two medications capable of fighting Ebola – as opposed to months or years that would be required for conventional research.

However, medical research is not limited to finding new drugs to fight disease. An important part of medical research studies the disease itself, in order to help prevent it from spreading further. Canadian start-up Meta uses AI to quickly read and comprehend scientific papers and then provide insights to researchers.

6) Virtual assistants

Virtual nursing assistants provide another avenue for application of AI in healthcare. AI solutions remotely assess a patient’s symptoms and deliver alerts to clinicians only when patient care is needed, reducing unnecessary hospital visits, and thereby lessening the burden on medical professionals. The latter saves 20 percent of a nurse’s time. Nuance Communications unveiled an artificial virtual assistant specifically for patients and healthcare providers. The company has built artificial intelligence virtual assistants for consumer and automotive brands including American Airlines, Amtrak, Audi, Barclay’s, BMW, Citi, Delta, Domino’s, FedEx, Ford, and GM.

Nuance’s state-of-the-art healthcare virtual assistant uses voice recognition technology, voice biometrics and text-to-speech, Electronic Health Record (HER) integrations and strategic health IT relationships to create a smart speaker designed specifically for healthcare cases.

7) Effective treatment

AI is enabling clinicians take a more comprehensive approach for disease management, better coordinate care plans and help patients to better manage and comply with their long-term treatment programmes. AiCure has created an application to monitor patients with long-term conditions and help them manage medication intake. The application uses visual recognition to identify the patient’s face, the medication they are taking, and confirm ingestion. The data is then sent back to the care provider or to a pharmaceutical company conducting a clinical trial. Another example is of a nursing-care robot, RoBear, that can lift and move patients in and out of bed into wheelchair, help those who need assistance to stand, and even turn patients in bed to prevent bedsores. Such transformation in delivery of patient care services helps in increasing the effectiveness of the treatment."
Antwort auf Beitrag Nr.: 57.599.319 von Popeye82 am 22.04.18 00:08:03"Founded in 2014, Prophesee has raised $37 million so far to develop a “neuromorphic vision system” that mimics the human eye and brain. Covered in our recent article “Watch for These 8 AI Startups Doing Computer Vision”, Prophesee’s technology provides an output equivalent to more than 10,000 frames per second, even in extreme lighting conditions, and manages to do this with high power efficiency and less data processing. That’s 10-100X better than the human eye, depending on who you ask. This efficiency gain is due to how their AI processes the images it sees. It looks only at changes, as opposed to taking thousands of pictures and comparing each one. Use cases include the following:




Using this technology, product designers can add multiple sensors without losing battery life and computational power, making Prophesee an ideal platform for connected, autonomous, and mobile applications in fields like automotive, robotics or industrial automation. Prophesee is currently evaluating the idea of implementing the same event-driven approach to radar and LiDAR outputs as well. "
http://www.prophesee.ai/
FIRST model that can replicate human performance on auditory tasks, such as identifying a musical genre


http://news.mit.edu/2018/machine-learning-system-processes-s…
Europe ALL-in on AI

http://www.reuters.com/article/us-britain-technology-ai/brit…
http://www.bloomberg.com/news/articles/2018-04-25/u-k-announ…
http://www.technologyreview.com/s/610379/heres-how-the-us-ne…
- The huge state investment is in stark contrast to America’s current AI policies.
The news: The UK has announced that it’s pouring $1.4 billion into British AI. Meanwhile, the European Commission has said that it wants to build a network of hundreds of research centers specializing in machine learning and robotics.
Why it matters: Europe lags America and China in building AI. The new moves are an attempt to play catch up—by training new researchers, retaining top talent, and creating an environment in which machine learning startups can prosper.
America, take note: Despite being a leader in the field, the US currently lacks formal policies to help foster AI research. There’s plenty it could do to change that. -


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