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Radiology is one of the most essential fields in clinical medicine. Experts in this field are specialists in deciphering and diagnosing disease based on various imaging modalities, ranging from ultrasound, magnetic resonance imaging (MRI), computerized tomography (CT), and x-rays. Studies have shown that the use of radiology in clinical practice has exponentially grown over the years: at the Mayo Clinic, between the years 1999 to 2010, use of CT scans increased by 68%, MRI use increased by 85%, and overall use of imaging modalities for diagnostic purposes increased by 75%, all numbers that have likely continued to rise, and indicate the sheer demand and growth of this robust field.

A unique proposal that has become prominent over the last few years to help alleviate this increased demand is the introduction of artificial intelligence (AI) technology into this field. Simply put, the premise of AI as an addition to the practice of radiology is straightforward, and has been envisioned in two main ways: 1) a system that can be programmed with pre-defined criteria and algorithms by expert radiologists, which can then be applied to new, straightforward clinical situations, or 2) deep learning methods, where the AI system relies on complex machine learning and uses neural-type networks to learn patterns via large volumes of data and previous encounters; this can then be used to interpret even the most complicated and abstract images.

Variety of body scans.

However, while much of the theoretical basis for AI in the practice of radiology is extremely exciting, the reality is that the field has not yet fully embraced it. The most significant issue is that the technology simply isnt ready, as many of the existing systems have not yet been matured to compute and manage larger data sets or work in more general practice and patient settings, and thus, are not able to perform as promised.Other issues exist on the ethical aspects of AI. Given the sheer volume of data required to both train and perfect these systems, as well as the immense data collection that these systems will engage in once fully mainstream, key stakeholders are raising fair concerns and the call for strict ethical standards to be put into place, simultaneous to the technological development of these systems.

Furthermore, the legal and regulatory implications of AI in radiology are numerous and complex. There are significant concerns in the data privacy space, as the hosting of large volumes of patient data for deep learning networks will require increased standards for data protection, cybersecurity, and privacy infrastructure. Additionally, given that AI systems will act as an additional diagnostic tool that must be accounted for in the patient encounter, legal frameworks will be required to fully flush out and navigate where liability falls in the case of misdiagnosis or medical negligence. Will this become an issue for the product manufacturer, or will there be a dynamic sharing of the responsibility by multiple parties? This will depend significantly on the amount of autonomy afforded to these systems.

However, radiologists must remain central to the diagnostic process. While AI systems may be able to detect routine medical problems based on pre-defined criteria, there is significant value provided by a trained radiologist that software simply cannot replace. This includes the clinical correlation of images with the physical state of the patient, qualitative assessments of past images with current images to determine progression of disease, and ultimately the most human aspect of medicine, working with other healthcare teams to make collaborative care decisions.

Using a human brain model to interpret MRI scans.

Indeed, there are significant potential benefits to the mass integration of certain AI systems into the practice of radiology, mainly as a means to augment a physicians workflow, especially given increasing radiology demands in clinical medicine. With some reports citing an expected rise in the use of AI in radiology by nearly 16.5% within the next decade, significant complexities remain unaddressed. However, these issues will ultimately need to be resolved in order to achieve a comprehensively capable and ethically mindful AI infrastructure that can become an integral part of clinical radiology.

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Artificial Intelligence Is Not Ready For The Intricacies Of Radiology - Forbes

The role AI plays in your life is a matter of choice (but only to a certain extent).

It doesnt seem too long ago that artificial intelligence (AI) was mostly the stuff of science fiction. Today it seems to be everywhere: in our home appliances, in our cars, in the workplace, even on our wrists.

To some extent, our use of AI is still a matter of personal choice. But because AI is becoming increasing ubiquitous, we need to make a lot of conscious decisions.

Regardless of the choices we make, we need to stay educated on the evolution of this science. A thoughtful primer on this is Rhonda Scharfs bookAlexa Is Stealing Your Job: The Impact of Artificial Intelligence on Your Future.

My conversation with Rhonda provides some good tips what we should know and what we can do.

Rodger Dean Duncan:AI today is similar to the introduction of the desktop computer three decades ago. Many people resisted computers and got left behind. Whats the best argument for AI today?

Rhonda Scharf

Rhonda Scharf:Artificial Intelligence is not going away. When the desktop computer was introduced in the 1980s, many people felt it was a fad, and it would disappear over time.

Hazel, a woman I worked with, was willing to bet her career on it.When the company I worked at insisted we transition to desktops or leave the company, she rolled the dice and called their bluff. She lost. She believed there was no way a company could exist without tried-and-true manual systems and that computers were a big waste of time and money.

We are in precisely that situation again.

If you can write instructions for a task so that someone can follow them, then AI can replicate those actions.

Duncan:So whats the implication?

Scharf:Not only can your company exist without you performing these tasks, it will also (eventually) be more profitable (with fewer errors) because of it.

By refusing to learn about AIand by refusing to adapt and be flexibleyoure rolling the dice that AI will not take over the tasks you currently do. Call yourself Hazel, and youll soon be out of a job.

AI is alive and well in the workplace, only many people dont realize it. Being nave and refusing to acknowledge what is right under your nose is a recipe for disaster. Take a look around at how much AI we already have in our lives. Artificial Intelligence is not going away. Adapt or become unemployed.

Duncan:Most people have grown comfortable with the idea of letting machines replace humans to do monotonous, heavy, repetitive, and dangerous tasks. But the notion of having AI make decisions and predictions about the future often evokes skepticism or even fear. What do you say to people who have such concerns?

Scharf:Movies like2001: A Space Odyessyand its AI character, HAL 9000, have planted the seeds of fear and mass destruction in our minds. We are afraid of what computers can do on their own. AI learns from its experiences and will make decisions on its owncalculated, logical, and statistically accurate decisions.

What AI doesnt do is make emotional decisions. Take AI stock trading as an example. Without any emotions involved, the robo-advisers can determine the optimal price to buy and sell specific stocks. They dont get emotionally tied into one more day and potentially lose profits. AI can evaluate millions of data points and make conclusions instantly that neither humans nor computers can do. As quickly as the market changes, AI changes its course of action based on the data.

Im not about to have AI make life-or-death decisions for me. The same way we now trust machines to handle monotonous, heavy, repetitive, and dangerous tasks, I will rely on AI to do some heavy thinking and bring me logical conclusions, quickly and efficiently.

If you don't want to be left behind, you'd better get educated on AI.

Duncan:What do you tell people who have privacy concerns about AI applications?

Scharf:The privacy concerns are real, but you gave up your privacy when you got your first mobile phone (for some this was as early as 1996). It could track you. Technically, that impacted your privacy 20-plus years ago.

Once the Blackberry was introduced in 1999, followed by the iPhone eight years later, your privacy became severely compromised. Your phone knows where you are, and it knows what youre doing. Even if you keep your Bluetooth off, your device and its apps know a lot about you.

If you wear any technology whatsoever, you are giving up your privacy. According to a 2014 study by GlobalWebIndex, 71% of people ages 16 to 24 want wearable tech. That was over five years ago before we had much wearable technology.

In the same study, 64% of internet users aged 16 to 64 said theyve either already used a piece of wearable tech or were keen to do so in the future.

Fast forward five years, and half of Americans use fitness trackers daily. More than 96% of Americans have a cell phone of some kind.

People may say they have privacy concerns, but when it comes to using technology that improves our lives, we forgo privacy for convenience.

Next: Artificial Intelligence, Privacy, And The Choices You Must Make

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What Role Will (Or Does) Artificial Intelligence Play In Your Life? - Forbes

Artificial intelligence is all the rage, and theres good money to be made in an industry thats still largely emerging from its infancy. But, the problems that AI solves are not easy, and to work in the AI industry you will need a strong and focused set of skills.

Heres the good news: We live in a society where a shocking number of people would rather have a robot boss than a human one. We would rather be led by machines.

This means that most of us are accepting of the idea of artificial intelligence, or AI.

In many sectors, machines have already taken over monotonous jobs. Manufacturing is a prime example. Auto and aerospace manufacturers use machines heavily in their assembly lines. In fact, machines completely transformed the way that our cars are built.

Artificial intelligence isnt just a fad. Its here to stay.

And, that means the industry will need a skilled workforce to build, test and deploy more and more artificial brains around the world. Get in early and youll stand to make a lot of money.

Not to mention help change the world.

If you are interested in a career in artificial intelligence, then youre in the right place.

Artificial intelligence attempts to mimic (and surpass) the power of the human brain using nothing but machines. Machine learning is another common term in AI.

The primary goals of artificial intelligence are:

Artificial intelligence attempts to build machines that think and reason rather than operate in a relatively confined space with pre-built routines, procedures and outcomes. Smart AI systems recognize patterns and remember past events and learn from them, making each subsequent decision smarter, logical and more organic.

AI is a giant paradigm shift in modern computing and requires a deeply scientific and logical approach to design computer systems that think and learn. In other words, build robots that arent just robots.

And believe it or not, AI capabilities are all over the place.

A few examples of artificial intelligence systems include speech recognition (available on many cell phones and smart home devices), email spam blockers, plagiarism checkers, language translation services (like Google Translate) and the auto-pilot system on airplanes.

Companies like Google, Microsoft, Apple, Amazon, Facebook, Accenture, Boeing and so many others are hiring for artificial intelligence roles. AI salaries are typically higher than average because good AI talent can be hard to find.

Artificial intelligence is everywhere in society, and the industry is growing rapidly in 2020. Here is exactly what you need to know to pursue a career in AI.

Artificial intelligence is highly scientific. After all, mimicking the human brain using machines is a very tough problem to solve, much less master. The skills that you will need to pursue AI as a career are varied, but all of them require a great deal of education, training and focus.

That said, there is a wide variety of career types available in AI and machine learning, and they range from higher-level research to low-level programming and implementation.

For example, researchers use their breadth of knowledge in theory and study to reveal new types of systems and capabilities. Researchers hypothesize new or different ways for machines to think and test their research for real-world feasibility.

Algorithm developers take AI research and transform that research into repeatable processes through mathematical formulas that can be implemented using hardware and software.

Software developers and computer scientists use those algorithms to write sophisticated pieces of software that analyze, interpret and make decisions.

Hardware technicians build pieces of equipment (like robots) to interact with the world. Robots use its internal software to move and operate.

Most careers in artificial intelligence require coursework and experience in a variety of math and science-related topics like:

Want a career in AI? Then read. A lot.

Read papers and case studies. Experiment with technologies like Map-Reduce, PHP, MySQL, Postgres and Big Data, especially if you are targeting a computer science-related career in AI. Expose yourself to as many technologies as you can.

Pro tip: Browse through AI job opportunities. Read the job descriptions and especially the requirements to get a feel for specific qualifications that you need for that job.

For example, some might need experience in low-level programming languages like Python or MatLab. Others, especially in the healthcare industry, need expertise in data services like Spark and Blockchain.

Regardless of the type of job that youre after in artificial intelligence, there is no better way to figure out the exact skills you need than to read job requisitions and stay as up-to-date in the industry as possible.

Use the Job Search tool here on The Ladders to find AI and machine learning jobs.

Though the types of careers in the AI industry are varied, most professionals in AI possess five key skills and capabilities, regardless of their individual roles.

Most AI professionals:

Are highly critical thinkers. They take nothing at face value and are naturally curious. They believe in trial and error and must test and experiment before making a concrete decision.

Like to push the envelope. AI is all about pushing the boundaries. Pegging the capabilities of hardware and software to their max, always looking for more. More ways to improve existing systems. More ideas for inventing new ways to live.

Live naturally-curious lives. Always wanting to know more, artificial intelligence pros want to know how things work. They dont just look. They observe. They dont hear. They listen.

Dont get easily overwhelmed. They understand that artificial intelligence is highly technical, but also realize that venturing into uncharted waters is difficult and mysterious. They enjoy the process rather than getting frustrated by it.

Love math and science. AI is highly technical and its a natural good fit for those who are gifted and interested in hard sciences and mathematics.

Artificial intelligence is not just about replacing the human component of the industry. Its also about making it easier to make decisions based on observable patterns, use logic and reasoning to form conclusions and build pathways to boost efficiency and production.

It is not an easy discipline, but thats also why salaries in the AI industry are much higher than average. It takes the right type of person with the right skill set to excel.

Are you the type of person whos right for a career in AI? If you have many of these skill sets, then you just might be.

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These are the exact skills you need to get a job in artificial intelligence - Ladders

SAN FRANCISCO, Feb. 5, 2020 /PRNewswire/ -- The global artificial intelligence marketsize is expected to reach USD 390.9 billion by 2025, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 46.2% from 2019 to 2025. Artificial Intelligence (AI) is considered to be a revolutionary technological development and its integration across a host of applications is one of the key factors driving this market. Advances in image and voice recognition are driving the growth of the regional market. Improved image recognition technology is critical in enhanced drones, self-driving cars, and robotics.

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Read 100 page research report with ToC on "Artificial Intelligence Market Size, Share & Trends Analysis Report By Solution, By Technology (Deep Learning, Machine Learning), By End Use (Advertising & Media, Law, Healthcare), And Segment Forecasts, 2019 - 2025" at: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market

The two major factors fueling market growth are emerging Artificial Intelligence technologies and growth in big data espousal. Rising prominence of Artificial Intelligence is enabling new players to venture into the market by offering niche application-specific solutions. Furthermore, companies are engaging in industry consolidations in a bid to gain competitive advantages. For instance, in January 2017, Microsoft Corporation acquired Maluuba in order to advance in the deep learning and AI landscape. Existing solution providers are innovating their product portfolio to include both hardware and software solutions.

North America held the dominant share in the global AI market in 2018 thanks to the availability of high government funding, presence of leading players, and strong technical base. Asia Pacific, however, is anticipated to overtake North America to emerge as the leading regional market by 2025, registering the highest CAGR. This can be attributed to rapid improvements in information storage capacity, high computing power, and parallel processing, all of which have contributed to the swift uptake of Artificial Intelligence technology in end-use industries such as automotive and healthcare.

AI has the potential to reduce the burden on clinicians and provide an efficient tool to workforces for accomplishing their tasks in a better way. For instance, AI voice-enabled symptom checkers can better access a situation and assist patients to the emergency department when immediate treatment is required. Artificial Intelligence is expected to resolve around 20% of unmet healthcare demands.

Grand View Research has segmented the global Artificial Intelligence market based on solution, technology, end use, and region:

Find more research reports on Next Generation Technologies Industry, by Grand View Research:

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About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

Contact:Sherry JamesCorporate Sales Specialist, USAGrand View Research, Inc.Phone: +1-415-349-0058Toll Free: 1-888-202-9519Email: sales@grandviewresearch.comWeb: https://www.grandviewresearch.comFollow Us: LinkedIn| Twitter

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SOURCE Grand View Research, Inc.

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Artificial Intelligence Market Size Worth $390.9 Billion by 2025: Grand View Research, Inc. - Yahoo Finance

For Immediate Release: February 07, 2020

Today, the U.S. Food and Drug Administration authorized marketing of software to assist medical professionals in the acquisition of cardiac ultrasound, or echocardiography, images. The software, called Caption Guidance, is an accessory to compatible diagnostic ultrasound systems and uses artificial intelligence to help the user capture images of a patients heart that are of acceptable diagnostic quality.

The Caption Guidance software is indicated for use in ultrasound examination of the heart, known as two-dimensional transthoracic echocardiography (2D-TTE), for adult patients, specifically in the acquisition of standard views of the heart from different angles. These views are typically used in the diagnosis of various cardiac conditions.

Echocardiograms are one of the most widely-used diagnostic tools in the diagnosis and treatment of heart disease, said Robert Ochs, Ph.D., deputy director of the Office of In Vitro Diagnostics and Radiological Health in the FDAs Center for Devices and Radiological Health. Todays marketing authorization enables medical professionals who may not be experts in ultrasonography, such as a registered nurse in a family care clinic or others, to use this tool. 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.

According to the Centers for Disease Control and Prevention, heart disease is the leading cause of death in the United States, killing one out of every four people, or approximately 647,000 Americans each year. The term heart disease refers to several types of heart conditions. The most common type is coronary artery disease, which can cause heart attack. Other kinds of heart disease may involve the valves in the heart, or the heart may not pump well and cause heart failure.

Cardiac diagnostic tests are necessary to identify heart conditions. Among them are electrocardiograms (more widely known as an EKG or ECG), Holter monitors and cardiac ultrasound examinations. The software authorized today is the first software authorized to guide users through cardiac ultrasound image acquisition. The Caption Guidance software was developed using machine learning to train the software to differentiate between acceptable and unacceptable image quality. This knowledge formed the basis of an interactive AI user interface that provides prescriptive guidance to users on how to maneuver the ultrasound probe to acquire standard echocardiographic images and video clips of diagnostic quality. The AI interface provides real-time feedback on potential image quality, can auto-capture video clips, and automatically saves the best video clip acquired from a particular view. Importantly, the cardiologist still reviews the images for a final assessment of the images and videos for patient evaluation.

The Caption Guidance software currently can be used with a specific FDA-cleared diagnostic ultrasound system produced by Teratech Corporation, with the potential to be used with other ultrasound imaging systems that have technical specifications consistent with the range of ultrasound systems used as part of the development and testing.

In its review of this device application, the FDA evaluated data from two independent studies. In one study, 50 trained sonographers scanned patients, with and without the assistance of the Caption Guidance software. The sonographers were able to capture comparable diagnostic quality images in both settings. The other study involved training eight registered nurses who are not experts in sonography to use the Caption Guidance software and asking them to capture standard echocardiography images, followed by five cardiologists assessing the quality of the images acquired. The results showed that the Caption Guidance software enabled the registered nurses to acquire echocardiography images and videos of diagnostic quality.

The FDA is dedicated to ensuring medical device regulation keeps pace with technological advancements, such as todays marketing authorization. This February, the FDA is hosting a public workshop titled Evolving Role of Artificial Intelligence (AI) in Radiological Imaging and seeks to discuss emerging applications of AI in radiological imaging, including AI devices intended to automate the diagnostic radiology workflow, as well as guided image acquisition. Discussions will also focus on best practices for the validation of AI-automated radiological imaging software and image acquisition devices, which is critical to assess safety and effectiveness.

The FDA reviewed the device through the De Novo premarket review pathway, a regulatory pathway for low- to moderate-risk devices of a new type. Along with this authorization, the FDA is establishing special controls for devices of this type, including requirements related to labeling and performance testing. When met, the special controls, along with general controls, provide reasonable assurance of safety and effectiveness for devices of this type. This action creates a new regulatory classification, which means that subsequent devices of the same type with the same intended use may go through FDAs 510(k) premarket process, whereby devices can obtain marketing authorization by demonstrating substantial equivalence to a predicate device.

The FDA granted marketing authorization of the Caption Guidance software to Caption Health Inc.

The FDA, an agency within the U.S. Department of Health and Human Services, protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nations food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products.

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FDA Authorizes Marketing of First Cardiac Ultrasound Software That Uses Artificial Intelligence to Guide User - FDA.gov