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The Potential Pitfalls of Machine Learning Algorithms in Medicine

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Back in the 1990s an intrepid group of researchers out of the University of Pittsburgh set out to write a computer program that could do a better job than doctors of predicting whether serious complications would develop in patients who presented with pneumonia.1 Success may have been a long shot, but it was definitely a shot worth taking. After all, the researchers figured that if they pulled it off, they could both lower costs and improve patient outcomes in one fell swoop. So they built a neural network -- basically a computer program that responds dynamically to external inputs -- and turned it loose on a database covering three-quarters of a million patients in 78 hospitals across 23 states. The results were curious, to say the least. The program seemed to have determined that patients with pneumonia and asthma had better outcomes than those who did not have asthma.


How Blockchain, A.I. And Other Tech Trends Will Disrupt Healthcare In 2018

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The increased use of artificial intelligence and machine learning is shifting the paradigm of medical research and treatment. These advanced technologies are providing researchers real-time access to every white paper and clinical case study conducted on a genetic disorder. Being able to develop such an elaborate database of information allows researchers to not only understand the full scope of a medical condition, but further shorten the amount of time it takes to develop a cure. Founded in 2011 by Gunjan Bhardwaj and Guarav Tripathi, Innoplexus is a technology and product development company focused on solving complex challenges in the pharmaceutical and life sciences industries. Their end-to-end platform for Life Sciences research uses artificial intelligence to generate smart data and insights to assist in the discovery, clinical development and regulatory compliance of pharmaceutical medicine.


Global Bigdata Conference

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Since its creation, artificial intelligence (AI) has found use in many different industries, including healthcare. The amount of medical data is astronomically huge and the problem of systematizing, storing, and, above all, using such data is of the utmost importance. People have long hoped that someday, computers will make accurate diagnoses and eliminate medical errors. But no one has created an effective AI doctor yet. The Skychain project promises to revolutionize the healthcare industry, using AI and blockchain technology.


Future of AI revenue: Top 10 uses cases for next decade

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Artificial intelligence already impacts many aspects of our daily lives at work, at home, and as we move about. Over the next decade, analyst firm Tractica predicts that annual Global AI enterprise software revenue will grow from $644 million in 2016 to nearly $39 billion by 2025, and services related revenue should reach almost $150 billion. These functional areas are applicable to many use cases, industries, and generate benefits for both businesses and individuals. Here are the top ten use cases which will reap financial rewards for AI technology product and service companies, and a broad spectrum of benefits for everyone else. Self driving cars and other autonomous vehicles are consistently called the "next revolution" in transportation, technology, and some say in civilization in general.


Digital health helping cancer diagnosis - Pharmaphorum

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The FDA has been championing digital health of late with wide-ranging guidance that derives from the 21st Century Cures Act. This legislation acknowledges the potential that digital health has to make a difference in patient care, potentially leading to more precise therapies. Several developments this week show that the regulator is right to be excited about its potential. Some of the most exciting advances have come in the field of cancer – medical devices firm Angle has produced a new analysis showing that its liquid biopsy device Parsortix could be used instead of conventional tissue biopsies. Parsortix works by monitoring a patient's bloodstream for circulating cancer cells and the University of Southern California research adds to the body of evidence showing that liquid biopsies could replace invasive and unpleasant tissue biopsies in the future.


Microsoft announces private preview, partnerships for AI-powered health bot project

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Today, we're pleased to announce the private preview of a new AI-powered project from Microsoft's Healthcare NExT initiative which is designed to enable our healthcare partners to easily create intelligent and compliant healthcare virtual assistants and chatbots. These bots are powered by cognitive services and enriched with authoritative medical content, allowing our partners to empower their customers with self-service access to health information, with the goal of improving outcomes and reducing costs. So, if you're using a health bot built by one of our partners as part of our project, you can interact in a personal way, typing or talking in natural language and receiving information to help answer your health-related questions. Our partners, including Aurora Health Care, with 15 hospitals, over 150 clinics and 70 pharmacies throughout eastern Wisconsin and northern Illinois, Premera Blue Cross, the largest health plan in the Pacific Northwest, and UPMC, one of the largest integrated health care delivery networks in the United States, are working with us to build out bots that address a wide range of healthcare-specific questions and use cases. For instance, insurers can build bots that give their customers an easy way to look up the status of a claim and ask questions about benefits and services.


Research focused on the artificial intelligence in healthcare market to surge at CAGR of 43% by 2022 - WhaTech

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The market is projected grow at a CAGR of 43% Growing usage of big data in healthcare industry and imbalance between health workforce and patients is expected to drive the growth of the AI in healthcare market. The AI in healthcare market has been segmented on the basis of offering, technology, application, end-user industry, and geography. On the basis of offering, the market has been further segmented into hardware, software, and services. The AI in healthcare market is further segmented on the basis of technology into deep learning, querying method, NLP, and context aware processing. North America is expected to be the largest and fastest-growing market for AI in healthcare during the forecast period.


AI advances at detecting cancer -- but it can't see you now

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"It is the early days," Aidoc CEO Elad Walach says. "There's not enough research at this point. Deep learning has been commoditized generally but it hasn't been commoditized for the medical domain. The algorithms out there aren't good enough as is. We need a lot of R&D to make AI work in this space.


Why AI is becoming the disease detective

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AI also raises the prospect of affordable healthcare for all. According to the World Health Organization (WHO), 400 million people do not have access to one or more essential health services, and 6% of those in low and middle-income countries are pushed further into extreme poverty because of health spending. In the future, we will see physicians working in partnership with AI – enabling technology to free up their time to concentrate on treatment of the disease as opposed to the diagnosis. Here we look at areas where AI promises to have a real impact on chronic and infectious diseases, from diagnosis and treatment plans to containing the global outbreaks of the likes of SARs and Ebola. Nearly 18 million people die each year from cardiovascular disease, according to WHO.


Microsoft announces preview of AI-powered health chatbot system

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Checking for care The project is being developed as part of Microsoft's Healthcare NeXT initiative. The company's trying to find ways of offering digital healthcare experiences that let user get immediate information on common ailments. Microsoft has partnered with Aurora Health Care for its latest chatbot service, creating the "Aurora Digital Concierge" for patients. The smartphone app allows users to determine the level of care needed for their condition. By answering questions provided by the bot, the app can suggest possible causes for the symptoms being experienced.