Artificial Intelligent

Insurers are using artificial intelligence and machine learning to review medical records, optimize care for chronic conditions, identify risk.

The machine learning algorithm, which can anticipate how cells respond CRISPR-induced breaks, could help researchers repair gene mutations.

IT leaders should show the value of specific AI use cases, while also ensuring the C-suite understands the potentially slow or hard-to-define ROI.

The team used convolutional neural networks on its own chest X-rays as well as imaging from NIH and Indiana University and said they did not perform equally.

If you think the digitisation of nursing is just about nurses filling out scores on a mobile device, it’s time to think again because artificial intelligence (AI) could be about to revolutionise the way nurses do their jobs. Recent digital developments include bottles which automatically issue reminders to drink, diapers that sound an alert when wet and sensor-equipped stoma pouches.   Heiko Mania, NursIT CEO, and a former nurse, believes AI will change the focus of nursing care: “Modern nursing expert software not only streamlines nursing documentation, it will automate it using AI, sensors and smart nursing aids. At the same time, professional nursing care will change from reactive to predictive, preventive nursing care.” Mania said they had developed a nursing care expert system, CareIT Pro, which supports automation in nursing. He explained that smart algorithms and AI could reduce the need for information to be entered and could link content, so that further workflows and tasks could be automatically initiated at the right time. He added that the software automatically recognised patterns, evaluated the planned nursing goals and recommended necessary adaptations. Webinar: AI: Evaluating Opportunities for Healthcare Providers He said sensors, wearables and smart devices were also enabling increased automation: “Intelligent tools automatically deliver data on the patient to the nursing expert software and thus allow automated documentation. Alarms, nursing tasks and digital processes can be generated and started independently. Nursing staff not only receive digital to-do lists, but can also see the current status and quality of the nursing processes at all times and react to them at an early stage. An intelligent drinking cup can automatically fill the drinking protocols and remind the patient to drink regularly or the stoma pouch sensor generates an automatic care task for changing the bag when it is almost full. We are currently developing an intelligent nursing mattress with a partner company that can detect not only the patient’s movement, breathing, position, pressure and sleep, but also incontinence.”  Improved quality of care and patient safety If the Internet of Things (IoT) is set to transform nursing, it is also starting to change the way nursing is taught. Widener University in Pennsylvania has introduced a range of simulation training from programming intravenous pumps and pumps for medication to updating electronic health records.  It also runs disaster simulation training as Widener, in line with other nursing schools, has recognised the need to prepare nurses for such incidents in the wake of 9/11. Nancy Laplante, Associate Professor of Nursing at Widener University, has recently published a paper arguing the case for introducing IoT in disaster training. Laplante believes this would highlight the application of these technologies in a meaningful way and enhance the experience for nursing students. She would like to teach the students to use mobile apps to track patients, triage them and track them to different hospitals, rather than using, for example, old-school paper-tagging of victims.    She said that downloading simple drawings, like Rich Pictures and Use Case Diagrams, which show all the participants in the disaster scene at a glance, can also improve understanding: “We were looking at what we call this rich picture for disaster scenarios and it was one way to help visualise all the interactions that would occur.  What we wanted to do was to give students an understanding of how complex communication is in a mass casualty disaster scenario. It is not just nurses talking to patients; they are going to have to deal with fire fighters, police officers, bystanders and health providers that are off site.”  Laplante said students had to get to grips with new technology as it was a growth area. She said that nursing students had to understand, embrace and help develop new solutions as they could transform their practice. However, she pointed out that while IT was an important aspect of nursing, it could never take the place of nurses: “I don’t personally believe that nurses can ever be replaced because you always need that human touch. My hope and my feeling for technology is that it can help enhance our care.”  It is likely that technology will fundamentally change nursing over the coming years and, provided it is used correctly, it seems it really could improve the quality of care and lead to increased patient safety.   .jumbotron{ background-image: url("http://www.healthcareitnews.com/sites/default/files/u2556/AIJumbotron.jpg"); background-size: cover; color: white; } .jumbotron h2{ color: white; } Focus on Artificial Intelligence In November, we take a deep dive into AI and machine learning.

Five new AI centres will be created in London, Leeds, Oxford, Coventry and Glasgow.    

A Chinese company, working with researchers in Sichuan and Boston, says its algorithm – similar to that enabling self-driving vehicles – could be a second set of eyes for polyp detection.

AI, machine learning, cognitive computing, neural networks? Supervised, unsupervised, semi-supervised? Object recognition, natural language processing? What does it all mean?

Savvy hospitals like Boston Children’s and NHS facilities are working with chatbot startups to create new ways to interface with patients seeking care.

Artificial intelligence (AI) is increasingly permeating medical imaging, but its integration into clinical practice will depend on the capacity of AI technology to facilitate workflow. How far has radiology advanced on this path? Insights asked a leading expert to find out.