Health Care Providers & Services


Machine Learning Helps Predict Critical Circulatory Failure

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A new study shows that an artificial intelligence (AI) method that fuses medically relevant information enables critical circulatory failure to be predicted in the intensive care unit (ICU) several hours before it occurs. Developed at the Swiss Federal Institute of Technology (ETH; Zurich, Switzerland) and Bern University Hospital (Inselspital; Switzerland), the early-warning platform integrates measurements from multiple systems using a high-resolution database that holds 240 patient-years of data. For the study, the researchers used anonymized data from 36,000 admissions to ICUs, and were able to show that just 20 of these variables, including blood pressure, pulse, various blood values, the patient's age, and medications administered were sufficient to make accurate predictions. In a trial run of the algorithms developed, they were able to predict 90% of circulatory-failure events, with 82% of them identified more than two hours in advance. On average, the system raised 0.05 alarms per patient and hour.


Rethinking Financial Services with Artificial Intelligence Tools

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Applying artificial intelligence to everything we're comfortable doing in banking is much easier than changing how we do things -- which would make the greatest use of AI. Few in financial services would argue that the future belongs to those institutions that harness data-driven machine intelligence to do more, better and faster. The insights and efficiencies needed to compete and thrive will come from AI-driven service personalization and optimization. But AI should do more than speed up a financial assembly line. As Ernst & Young stated in a report: "AI-driven financial health systems will become personal financial operating systems. Consumer finance will unbundle products and rebundle personalized and holistic value propositions based on life events."


Challenges of Artificial Intelligence in Healthcare -- Inovalon

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Artificial intelligence has become an intricate part of our everyday lives. We encounter it consciously and subconsciously -- at the grocery store, when we call customer service, and even in our homes and cars. With an increasing reliance on a technology designed to constantly collect our data – one that is programmed to be "smarter" than the human brain – are we leaving ourselves open to significant issues such as data breaches or information misuse in the future? How can we mitigate the potential challenges posed by artificial intelligence in healthcare and other industries? The emergence of artificial intelligence in healthcare has brought about countless opportunities for improved patient care outcomes, machine learning-assisted care, and deep learning technological advancements.


Council Post: Virtual Patient Care Using AI

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Conversational AI technology continues to improve as we move "beyond the screen," and the changes in human-computer interaction will be immense and transformative. Healthcare is an industry that can be transformed from the bottom up as a result of this technology. I believe the impact of conversational AI will be felt most in the area of virtual care. Just as retail moved from brick-and-mortar stores a few decades ago, healthcare is having its moment with AI technologies ushering in a new age where virtual patient care -- from appointment scheduling to urgent care direction and medication management -- is possible using virtual care tools based on conversational AI. UCHealth, nonprofit health system based in Aurora, Colorado, and Avaamo client, is a good example of where the industry is headed.


Frimley Park Hospital installs new 'deep learning' CT scanners

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The algorithm, which is integrated with three new Canon CT scanners installed at Frimley Health NHS Foundation Trust, has been trained to differentiate'noise' from true signal, reducing distortions and maintaining details in image outputs.


Data and AI: The future of healthcare

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What are the key trends to take note of in the future of healthcare? How can the NHS improve its rates of adoption and integration? Today, the healthcare sector generates and has access to more data than ever before. Big data and artificial intelligence have the potential to revolutionise how we predict and prevent disease before patients get ill, improve treatment, and change how we make scientific discoveries and develop new medicines. At AstraZeneca, our vision is a future of individualised healthcare solutions focused on improved patient outcomes, driven by science and data.


Data and AI: The future of healthcare

#artificialintelligence

What are the key trends to take note of in the future of healthcare? How can the NHS improve its rates of adoption and integration? Today, the healthcare sector generates and has access to more data than ever before. Big data and artificial intelligence have the potential to revolutionise how we predict and prevent disease before patients get ill, improve treatment, and change how we make scientific discoveries and develop new medicines. At AstraZeneca, our vision is a future of individualised healthcare solutions focused on improved patient outcomes, driven by science and data.


Artificial intelligence for fraud detection is bound to save billions

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Fraud mitigation is one of the most sought-after artificial intelligence (AI) services because it can provide an immediate return on investment. Already, many companies are experiencing lucrative profits thanks to AI and machine learning (ML) systems that detect and prevent fraud in real-time. According to a new report, Highmark Inc.'s Financial Investigations and Provider Review (FIPR) department generated $260 million in savings that would have otherwise been lost to fraud, waste, and abuse in 2019. In the last five years, the company saved $850 million. "We know the overwhelming majority of providers do the right thing. But we also know year after year millions of health care dollars are lost to fraud, waste and abuse," said Melissa Anderson, executive vice president and chief audit and compliance officer, Highmark Health.


Healthcare professionals need training in AI, says report -

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There is an urgent need to attract, educate, and train a generation of data literate healthcare professionals while training the current workforce to realise the potential of artificial intelligence (AI), according to a new report. The report explores the impact of AI on the future of European healthcare and its workforce. It highlights the need to define new organisational models and skills that healthcare professionals will need to support the adoption and scaling of the technology, and outlines the new types of talent that will need to be attracted. The report from EIT Health and McKinsey found that basic digital skills, biomedical and data science, data analysis, and the fundamentals of genomics will be critical, if AI and machine learning is to penetrate healthcare services. Authors noted that the WHO estimates that by 2030 the world will be short of 9.9 million doctors, nurses and midwives, which adds further urgency to address the challenge of already overburdened health systems.


AI success depends on good datasets, strategic alignment 7wData

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Given all the relentless hype about its Artificial Intelligence and its transformative potential for healthcare, it would be understandable if some health systems might be casting about in search of AI or machine learning projects they could try. But that sort of rushed, ad hoc approach is precisely the wrong one to take, says Tushar Mehrotra, senior vice president of analytics at Optum. "The only way you are going to get value out of AI is to link the clinical or business problem to the organization's overall strategy and make sure you have a rich enough data set to train the model so it generates actionable insights," said Mehrotra. "Making sure you are building and designing your AI effort the right way means putting in the work up front to create a clear understanding of what you are trying to solve so it can be embedded in the decision-making workflow," he said. "Too often, AI projects start with a quest for academic insight."