The advent of large data sets from many sources (big data), machine learning, and artificial intelligence (AI) are poised to revolutionize asthma care on both the investigative and clinical levels, according to an article published in the Journal of Allergy and Clinical Immunology. During 15-minute clinic visits, only a short amount of time is spent understanding and treating what is a complex disease, and only a fraction of the necessary data is captured in the electronic health record. "Our patients and the pace of data growth are compelling us to incorporate insights from Big Data to inform care," the researchers posit. "Predictive analytics, using machine learning and artificial intelligence has revolutionized many industries," including the healthcare industry. When used effectively, big data, in conjunction with electronic health record data, can transform the patient's healthcare experience.
The theme for the Private Healthcare Summit 2020 is "The transformation of private healthcare in a decade of change" The next ten years will see a radical shift in private healthcare - breakthroughs in Artificial intelligence and digital health, the consumerisation of private healthcare, a volatile market, the drive for improved outcomes and reduced costs. The 2020 Summit will feature contributions from the opinion leaders and entrepreneurs who will lead the industry's response to change The conference will explore the following topics: • The development of AI and its potential impact on the private healthcare sector.
Diabetes Professional Care Charity of the year, X-PERT Health, has appointed digital healthcare agency, Pulse, to transform their ground-breaking diabetes education programme onto a digital platform. The new platform, which will be accessible via an app or website, will enable X-PERT Health to scale up its current group based programme, allowing hundreds of thousands more patients to develop the knowledge, understanding and confidence to make lifestyle changes to prevent or manage Type 2 diabetes, further strengthening X-PERT Health's'educate not medicate' philosophy. The educational content will be interactive and engaging, including animated videos, games and quizzes to support discovery learning in a fun and easy-to-use way. The digital programme will also include features such as real-time tracking for diet, physical activity, health results, medication requirement and mood and sleep – helping users to manage and improve their lifestyle and health. This information can then be shared with the users' healthcare professional as part of their regular check-up.
Researchers have successfully applied AI in radiology to identify findings either detectable or not by the human eye. Radiology is now moving from a subjective perceptual skill to a more objective science.2,3 In Radiation Oncology, AI has been successfully applied to automatic tumor and organ segmentation,4–6 78 and tumor monitoring during the treatment for adaptive treatment. In 2012, a Dutch researcher, Lambin P, proposed the concept of "Radiomics" for the first time and defined it as follows: the extraction of a large number of image features from radiation images with a high-throughput approach.9 As AI became more popular and also more medical images than ever have been generated, these are good reason for radiomics to evolve rapidly.
You may think that artificial intelligence (AI) will make doctors obsolete soon but that day is still far off. In fact, computers are not that intelligent just yet. Most computer solutions emerging in healthcare rely on algorithms written to analyse data and recommend treatments. They do not rely on computers thinking independently. The computers in question are fed with large amounts of known data and use rules or algorithms set by experts to extract information and apply it to a health issue or problem.
If you ask the average person for a working definition of artificial intelligence (AI), you're likely to receive a slew of answers that boil down to the same concept: robots. Most nonexperts are still receiving their information on AI from science fiction films and clickbait articles with headlines adjacent to "Machines to Replace Humans by 2030." It's no wonder, then, why patients would be apprehensive toward AI in a hospital setting. They want a doctor to handle their treatment, not a computer. But what these patients don't often know is that AI is already being used in hospitals globally.
As healthcare provider organizations confront the steep challenge of securely and efficiently bridging the digital gaps among various technology systems, many are looking to cloud technologies that empower interoperability, marry healthcare information systems with AI, and ensure the privacy and security of patient data. With this in mind, Healthcare IT News turned to Concord Technologies, a cloud fax and document process automation company (it will be in booth 634 at HIMSS20 in March), to look ahead at 2020 and identify three trends with AI-based cloud fax technology. The CAQH Index shows a $9.8 billion savings opportunity for the healthcare industry by reducing the administrative burden found in eligibility and benefit verification, prior authorization, claim submission, coordination of benefits or a crossover claim, claim status inquiry, claim payment, and remittance advice. CAQH is a non-profit alliance of health plans and trade associations developing and leading initiatives designed to positively impact the business of healthcare. In 2020, AI-enabled technologies will transform administrative workflows across digital channels, reducing administrator and clinician burnout and improving overall staff satisfaction, said John Harrison, senior vice president at Concord Technologies.
FirstWord MedTech's Digital Ten is a fortnightly round-up of the 10 most read and noteworthy headlines related to digital health, including industry deals, alliances, collaborations, innovations and R&D news. The biggest M&A deal inked this year so far comes from the telemedicine field with Teladoc Health agreeing to fork out $600 million to acquire InTouch Health, a provider of cloud-based telemedicine software and physician services for hospitals and health systems. Teladoc's existing telehealth service platform targets consumers and with this deal, it will gain a complementary business that is expected to generate revenue of $80 million in 2019, representing 35% year-over year growth, and a new facility-based virtual care platform. Mojo Vision's smart contact lens receives FDA breakthrough device designation In yet another first for 2020, Mojo Vision's Mojo smart contact lens is the first ophthalmic product to get FDA breakthrough device designation this year. The lens incorporates what the company describes as the "smallest and densest dynamic display ever made," along with a power-efficient image sensor optimised for computer vision, a custom wireless radio, and motion sensors for eye-tracking and image stabilisation.
Artificial intelligence (AI) company qure.ai is testing its application for chest X-Rays to detect tuberculosis (TB) with mobile TB screening programs in several developing countries. However, one issue the company encountered was the lack of PACS systems to run the software or the lack of internet connections in rural areas. This black box is a mini-server/computer the company provides to allow remote clinics a platform to run the AI and house the digital images.
Researchers have designed an unprecedented method that is capable of improving brain images obtained through magnetic resonance imaging using artificial intelligence. This new model manages to increase image quality from low resolution to high resolution without distorting the patients' brain structures, using a deep learning artificial neural network -a model that is based on the functioning of the human brain- that "learns" this process. The study was published in the scientific journal Neurocomputing. "Deep learning is based on very large neural networks, and so is its capacity to learn, reaching the complexity and abstraction of a brain", explains researcher Karl Thurnhofer, main author of this study, who adds that thanks to this technique, the activity of identification can be performed alone, without supervision; an identification effort that the human eye would not be capable of doing. This study represents a scientific breakthrough, since the algorithm developed by the UMA yields more accurate results in less time, with clear benefits for patients.