Public Health


Canon Medical's 3T MR System Receives FDA Clearance for Artificial Intelligence-Based Image Reconstruction Technology BioSpace

#artificialintelligence

WIRE)-- Canon Medical Systems USA, Inc. has received 510(k) clearance on its Advanced intelligent Clear-IQ Engine (AiCE) for the Vantage Galan 3T MR system, further expanding access to its new Deep Learning Reconstruction (DLR) technology. This technology, which is also available across a majority of Canon Medical's CT product portfolio, uses a deep learning algorithm to differentiate true MR signal from noise so that it can suppress noise while enhancing signal, forging a new frontier for MR image reconstruction. AiCE was trained using vast amounts of high-quality image data, and features a deep learning neural network that can reduce noise and boost signal to quickly deliver sharp, clear and distinct images, further opening doors for advancements in MR imaging. "AiCE utilizes a next generation approach to MR image reconstruction, further proving Canon Medical's leadership and commitment to innovation in diagnostic imaging," said Jonathan Furuyama, managing director, MR Business Unit, Canon Medical Systems USA, Inc. "With the expansion of this unique DLR method across modalities and into MR, we're elevating diagnostic imaging capabilities for our customers by bringing the power of AI to routine imaging to provide more possibilities in improving patient care than ever before." Canon Medical Systems USA, Inc., headquartered in Tustin, Calif., markets, sells, distributes and services radiology and cardiovascular systems, including CT, MR, ultrasound, X-ray and interventional X-ray equipment.


The case for open data for AI in the fight against COVID-19

#artificialintelligence

Death rate may be a poor metric. If it's very high for 80 years old people, this is a group where death can occur any time due to the next cold or flu for example. A better metric is life span reduction. In an 80-year old with health issues, life span reduction might just be a few weeks. Also, I assume many people already caught it and recovered without being aware of ever catching it, and they are unaccounted for in the statistics if they didn't go to the doctor and were not properly tested.


The case for open data for AI in the fight against COVID-19

#artificialintelligence

Death rate may be a poor metric. If it's very high for 80 years old people, this is a group where death can occur any time due to the next cold or flu for example. A better metric is life span reduction. In an 80-year old with health issues, life span reduction might just be a few weeks. Also, I assume many people already caught it and recovered without being aware of ever catching it, and they are unaccounted for in the statistics if they didn't go to the doctor and were not properly tested.


Machine Learning

#artificialintelligence

After years of development, machine learning methods have matured enough to be used in clinical medicine. In 2018 the FDA approved software to screen patients for diabetic retinopathy, and the methods are rapidly making their way into other applications for image analysis, natural language processing, EHR data mining, drug discovery, and more. JAMA is proud to be a primary forum for the work of interdisciplinary groups demonstrating the use of machine learning methods for clinical medicine and health care. To understand the work read JAMA's Users' Guide to the Medical Literature How to Read Articles That Use Machine Learning, authored by Google Health scientists, and an accompanying commentary. See also JAMA Network's Health Informatics collection.


Where top VCs are investing in medical and surgical robotics – TechCrunch

#artificialintelligence

The medical and healthcare categories have been leading robotic innovation for decades. Look no further than Intuitive Surgical, whose da Vinci robot has been performing surgery since it received FDA clearance in the early 2000s. These days, the SRI spinoff is currently valued at more than $60 billion. There's a lot of money to be made for established companies and still areas to be explored for young startups, both on and off the operating table. The venture community has been betting big on companies developing everything from new surgical robots, assistive robots for medical facilities, robotic medical aid devices or otherwise.


Artificial intelligence can help forecast suicide rates. Here's how.

#artificialintelligence

The Centers for Disease Control and Prevention (CDC) is using data from platforms like Reddit and Twitter to power artificial intelligence that can forecast suicide rates. The agency is doing this because its current suicide statistics are delayed by up to two years, which means that officials are forming policy and allocating mental health resources throughout the country without the most up-to-date numbers. The CDC's suicide rate statistics are calculated based on cause-of-death reports from throughout the 50 states, which are compiled into a national database. That information is the most accurate reporting we have, but it can take a long time to produce. "If we want to do any kind of policy change, intervention, budget allocation, we need to know the real picture of what is going on in the world in terms of people's mental health experiences," Munmun de Choudhury, a professor at Georgia Tech's School of Interactive Computing who is working with the CDC, told Recode.


JUUL patents AI-powered device to curb addiction by releasing smaller amounts of nicotine

Daily Mail - Science & tech

JUUL has been called'highly addictive', but the firm may be developing a new product that helps users kick the habit once and for all. The San Francisco company filed a patent that describes an artificial intelligence powered product that delivers fewer nicotine amounts to the user by learning their smoking habits over time. The document highlights a device that alternates between nicotine and a non-nicotine product in order to gradually reduce the intake of the drug. The device may also be connected to a smartphone that could log how much nicotine is being consumed, allowing the device to determine how it should regulate the drug, as first reported on by The Logic. JUUL started off as a way of providing the world's one billion smokers with an alternative to combustible tobacco products.


How AI and machine learning are transforming clinical decision support

#artificialintelligence

"Between 12 to 18 million Americans every year will experience some sort of diagnostic error," said Paul Cerrato, a journalist and researcher. "So the question is: Why such a huge number? And what can we do better in terms of reinventing the tools so they catch these conditions more effectively?" Cerrato is co-author, alongside Dr. John Halamka, newly minted president of Mayo Clinic Platform, of the new HIMSS Book Series edition, Reinventing Clinical Decision Support: Data Analytics, Artificial Intelligence, and Diagnostic Reasoning. At HIMSS20, the two of them will discuss the book, and the bigger picture around CDS tools that are fast being transformed by the advent of artificial intelligence, machine learning and big data analytics.


FDA OKs first-of-a-kind AI that guides cardiac imaging - MedCity News

#artificialintelligence

The FDA has cleared what it describes as the first software that uses AI to guide family doctors, registered nurses and other clinicians in taking cardiac ultrasounds. Developed by Brisbane, California-based Caption Health, the software communicates instructions via prompts on a screen-based interface. The prompts allow non-experts to capture images and videos of diagnostic quality. "This is especially important because it demonstrates the potential for artificial intelligence and machine learning technologies to increase access to safe and effective cardiac diagnostics that can be life-saving for patients," Robert Ochs, a deputy director in the FDA's Center for Devices and Radiological Health, said in a statement. The software is called Caption Guidance and was cleared for use with a diagnostic ultrasound system developed by Teratech Corp., though the software has the potential to be used with other systems, according to the FDA.


FDA Grants Caption Health Landmark Authorization

#artificialintelligence

Caption Health, a leading medical AI company, announced that the US Food and Drug Administration (FDA) authorized marketing of Caption Guidance, software that assists medical professionals in the acquisition of cardiac ultrasound images. Caption Guidance uses artificial intelligence to provide real-time guidance and diagnostic quality assessment of images, empowering healthcare providers--even those without prior ultrasound experience--with the ability to capture diagnostic quality images. Empowering more clinicians with ultrasound image acquisition capability will bring the benefits of ultrasound to more patients, help standardize the quality of care, and help institutions realize valuable cost and time savings. Caption Guidance was authorized via the De Novo pathway, a regulatory pathway reserved for novel technologies. The granting of this De Novo is groundbreaking, as Caption Guidance is the first medical software authorized by the FDA that provides real-time AI guidance for medical imaging acquisition.