By leveraging Data Science, AI, and other digital technologies, the healthcare industry could build complementary health solutions that are personalized to the specific needs of patients. Here is how and why. The world population grows by more than 80 million per year, according to a 2017 report by the United Nations. By 2050, there will be 10 billion people on this planet and people over the age of 60 years and above are expected to double. It's clear that a growing and aging world population needs better and more sustainable solutions for health and nutrition.
Edwards Lifesciences is delving deeper into the realm of artificial intelligence through a partnership with San Francisco-based Bay Labs. The goal of the collaboration, which has multiple initiatives is to improve the detection of heart disease. Some of the initiatives include, the development of new AI-powered algorithms in Bay Labs' EchoMD measurement and interpretation software suite; support for ongoing clinical studies at institutions; and the integration of EchoMD algorithms into Edwards Lifesciences' CardioCare quality care navigation platform. Irvine, CA-based Edwards' CardioCare program combines clinical consulting expertise with a cloud-based platform to facilitate in the identification, referral, and care pathway management of patients with structural heart disease. CardioCare can help hospitals improve quality by reducing variability in echocardiography and ensure effective communication between care settings to ensure patients access to care.
Artificial intelligence is poised to change the pharmaceutical and healthcare industries as it looks to streamline, speed-up and improve overall efficiency. It might still be early days but it's a bandwagon that organisations are quickly jumping on board. According to a CB Insights report, about 86% of healthcare organisations, life science companies and med tech firms were using artificial intelligence technology in 2016. Big pharma names announcing deals and applications include Bayer, J&J, Merck, Sanofi, Genentech and Pfizer. Meanwhile, more than 50% of healthcare industry executives anticipate broad-scale adoption of the technology by 2025, a TechEmergence study recently revealed, with nearly half of the respondents noting that chronic conditions will be the initial target.
Bringing a new medical treatment to market is a slow, laborious process -- and for a good reason: patient safety is the top priority. But when recruiting patients to test promising treatments in clinical trials, the faster the better. "Many people in medicine have ideas of how to improve healthcare," said Wout Brusselaers, CEO of Pasadena, Calif.-based startup Deep 6 AI. "What's stopping them is being able to demonstrate that their new process or new drug works, and is safe and effective on real patients. For that, they need the clinical trial process."
Israeli radiology startup Aidoc has received FDA clearance for its AI-based product meant to help identify potential cases of pulmonary embolism in chest CT scans. Pulmonary embolism (PE) – which occurs when a blood clot gets lodged in the lung – is considered a silent killer that causes up to 200,000 deaths a year in the United States. The condition often strikes with little to no warning and diagnosis of a case can be extremely time-sensitive. Aidoc's technology doesn't require dedicated hardware and runs continuously on hospital systems, automatically ingesting radiological images. The 70-person company focuses on workflow optimization in radiology to help triage high risk patients for additional and faster review.