Startups from around the world are innovating in the ways artificial intelligence can be brought to bear in the healthcare space, with clinical, financial and operational applications, as evidenced by new launches from two AI companies with roots in Israel. This week, Netanya-based CLEW Medical, launched its predictive analytics platform, which crunches real-time data with machine learning technology to drive quality and safety improvement and help control costs. The company, formerly known as Intensix, said the AI platform can help health systems prevent life-threatening complications across settings. It's been deployed in intensive care units already, and CLEW aims to expand the technology's applications, giving staff insights to help streamline medical care. Officials pointed out that inpatients often come with some 300 unique data elements to be tracked, some measured every few milliseconds.
Publications like The Wall Street Journal, Forbes and Fortune have all called 2017 "The Year of AI." AI outperformed professional gamers and poker players in new realms. Access to deep learning education expanded through various online programs. The speech recognition accuracy record was broken multiple times, most recently by Microsoft. And research universities and organizations like Oxford, Massachusetts General Hospital and GE's Avitas Systems invested in deep learning supercomputers. These are a few of many milestones in 2017.
People use chatbots to find homes, interact with their favorite brands, and schedule appointments. Many consumers are onboard with using chatbots to gather instant, personalized information. In many cases, chatbots are the first point of contact for individuals who feel unwell and need to decide whether to head to the doctor. As this technology becomes more prominent, people understandably begin to wonder if insurance companies will cover sessions with chatbot doctors. Given their innovative use of chatbots in the health care sector, it's looking like insurers and health organizations in the U.K. could be the first to establish insurance coverage for health consultations with chatbots.
Early recognition of cardiac arrest is vitally important as the chance of survival decreases about 10 percent with each minute. In Denmark AI assistant Corti is listening in to phone calls to emergency services to help detect signs of a heart attack. With Corti implemented, the dispatcher gets a digital assistant that listens in on the conversation and helps to look for important signals in both verbal communication, as well as tone of voice and breathing patterns, while also considering other metadata. All the data provided during the emergency call is automatically analyzed by Corti and then compared to the millions of emergency calls – which Corti has already analysed –to find important patterns. As Corti's understanding of the incident increases, the assistant will try to predict the criticality of the patient's situation based on symptom descriptions and the signals gathered from voice and audio.
Using artificial intelligence to predict when patients may die sounds like an episode from the dystopian science fiction TV series "Black Mirror." But Stanford University researchers see this use of AI as a benign opportunity to help prompt physicians and patients to have necessary end-of-life conversations earlier. Many physicians often provide overly rosy estimates about when their patients will die and delay having the difficult conversations about end-of-life options. That understandable human tendency can lead to patients receiving unwanted, expensive and aggressive treatments in a hospital at their time of death instead of being allowed to die more peacefully in relative comfort. The alternative being tested by a Stanford University team would use AI to help physicians screen for newly-admitted patients who could benefit from talking about palliative care choices.
The state of value-based reimbursement efforts has been uncertain. Many healthcare organizations are indeed pursuing newer strategies to replace traditional fee-for-service care while reducing costs and improving quality, but progress has often been halting. Still, experts from Cedars-Sinai, CVS Health, Blue Cross NC and Harvard Pilgrim Health Care say they're quite optimistic for the future of value-based care in 2018 and beyond. In the area of health IT, the shift to value-based care is fueling new uses for data and has the potential to reinvigorate the electronic health records that many feared had gone stale, said Scott Weingarten, senior vice president and chief clinical transformation officer at Cedars-Sinai and an innovator in the value-based care space. "I believe that natural language processing, machine learning and artificial intelligence have the potential to significantly improve the interpretation, understanding and usefulness of information documented in the electronic health records and other information sources," Weingarten said.
Imagine lying on a hospital bed. One leans down to tell you that you are terribly sick and says they recommend a risky procedure as your best hope. You ask them to explain what's going on. Your trust in the doctors ebbs away. Replace the doctors with a computer program and you more or less have the state of artificial intelligence (AI) today.
What is Intel doing in the area of artificial intelligence/machine learning? Artificial intelligence is causing a technological revolution. Intel recognizes the power AI has to transform society and industries. We are committed to democratizing AI and machine-learning innovations so that everyone has the opportunity to benefit. To that end, we've been doing a number of things: This group focuses on solutions that make it easy to incorporate custom AI solutions into existing infrastructure.
The source of the common hospital-acquired infection known as C. diff can be hard to pin down in a busy, sprawling hospital, where patients might pick up the bug in countless locations. Hospitals nationwide are eager to reduce C. diff infections. A few years ago, when the UCSF Medical Center set a priority to cut rates of the infection, the UCSF Health Informatics team pitched an unusual strategy: Digitally reconstructing each patient's footsteps in the hospital. The team realized that within each patient's electronic health record (EHR) was detailed information about every room each patient had stepped into for every test. Using these digital breadcrumbs mined from the records, the team was able to trace a significant source of infection back to one CT scan machine.
Artificial Intelligence: Arterys AI has not had a bad year yet. Between breakthrough technologies and soaring funding rounds, there was no shortage of strong candidates to choose from in 2017. Ambra Health CEO Morris Panner, JD, gave the nod to Arterys. The 10-year-old San Francisco, California, company both started and ended 2017 in style. In January, it received a first-of-its-kind FDA approval for its cloud-based technology, which applies AI and deep learning to medical imaging analysis.