AI can reduce the need for CT scans, which expose patients to higher levels of radiation than other ... [ ] imaging techniques. AI's potential in medicine has already attracted large amounts of media and public attention. However, some of the specific uses and consequences of AI in the context of health care aren't particularly well known, at least not compared to awareness of the general utility of artificial intelligence. Some of these uses may be life-saving, and in more ways than one. In recent months, a small number of companies and researchers have begun using AI for the purposes of medical imaging, harnessing machine learning algorithms in order to construct 3D models out of 2D images.

We started with a simple question that investors could be asking about the Ericsson (NASDAQ:ERIC) stock: given a certain drop or rise, say a 5% drop in a week, what should we expect for the next week? Is it very likely that Ericsson will recover the next week? In fact, we found that if the Ericsson drops 5% in a week (5 trading days), there is a 21% chance that it will rise by 10% over the subsequent month (21 trading days). Want to try other combinations? You can test a variety of scenarios on the Trefis Machine Learning Engine to calculate if Ericsson stock dropped, what's the chance it'll rise.

Niccolo Mejia covers AI applications across industries at Emerj. He holds a bachelor's degree in Writing, Literature, and Publishing from Emerson College. Many of the largest US banks, including Bank of America, are starting to automate many of their business processes with AI. These include ACH payments and more specific processes such as order to cash. Bank of America has been investing seriously in AI and machine learning since at least 2017 and continues to research ways they can take advantage of AI in the future.

I covered the AI Summit in New York last week because I wanted to learn more about AI and Machine Learning. According to Tractica, AI is being implemented globally. AI and Machine Learning used in many verticals and processes. For example, when I compose an email using GMAIL, I received suggestions on how to finish a sentence. To use the GMAIL suggestion, I can tap the right arrow button on my keyboard.

Together with Prof. Dr. Christian Meske (FU Berlin) and Jodie Lobana (McMaster University, Hamilton, Canada), Dr. Niklas Kühl won the Paper-a-Thon at the International Conference on Information Systems (ICIS) 2019. The final topic was "Do you comply with AI? - The impact of personalized explanations of learning algorithms on compliance behavior". The paper focuses on machine learning algorithms as "black boxes" and addresses the situation that, based on different user backgrounds (experience, education, etc.), different mental models of reality and thus algorithms exist in organizational contexts. This requires a model-specific personalization of explanations ("Explainable AI"), which in turn have an influence on trust, compliance behavior and ultimately task performance. First results from a qualitative study support these assumptions, which will be tested quantitatively in a follow-up project.

Time is of the essence when it comes to treating cancer, the second leading cause of death in the U.S. according to the Centers for Disease Control and Prevention. Between diagnosis and the first day of treatment, days and even weeks may tick by as doctors convene to discuss treatment plans and order testing to gather as much information as possible. But as a new decade dawns, artificial intelligence may buy more time for those who need it most. Both President Donald Trump and former Vice President Joe Biden have promised to prioritize curing cancer should they win the 2020 election. But because of its complex biology, cancer has been historically difficult to cure with a pill or injection. As new treatments like immunotherapy undergo further research, health systems are starting to harness data-sharing and artificial intelligence to better predict a patient's prognosis, and determine the most effective treatment plan for their cancer based on other patients with similar medical histories.

Artificial intelligence (AI) is transforming the business landscape of the United States, allowing companies across different industries to streamline operations, optimize systems and leverage big data to make better decisions. Practically every day there seems to be a new breakthrough or a different application for AI, which makes things interesting for businesses that strive to stay ahead of the competition. Some businesses see AI as a magic bullet destined to address all their innovation problems, while others view it as a tool that must be handled with caution, especially given the increasing (and legitimate) attention being paid to the topic of the ethics in AI. While the reality of AI adoption depends on a spectrum of attributes that includes accuracy, explainability, ethics, regulations and technology democratization, to name a few, one thing is for certain: AI is here to stay. With that in mind, here are three AI trends businesses should address to stay competitive in the year ahead.

"The main thing is to keep the main thing the main thing." These wise words of world-renowned business author Stephen Covey challenge each of us as we stand on the precipice of a new decade. But what's the'main thing' when navigating technology as we enter 2020? The simple answer is… Cybersecurity. As innovation explodes into every area of our lives, cybersecurity is providing the glue that can enable the good and disable the bad for implementing cutting-edge innovation as well as reducing risk from older vulnerabilities. We also see cybersecurity continue as the top priority for chief information officers (CIOs) in 2020, just as it has been for most of the past decade, with groups like the National Association of State CIOs (NASCIO). But even as cybersecurity solutions offer a way forward to ensure privacy protections are workable and effective, most people see the data breaches, ransomware, identity theft, denial-of-service attacks and other cyberattacks as proof that cybersecurity has become the Achilles Heel, not the savior, for new innovation. Even as exciting advances occur in artificial intelligence (AI), autonomous vehicles, 5G networks cloud computing, mobile devices and the Internet of Things (IoT), these same developments seem to cause negative societal disruptions that make daily news headlines. So what will happen next with cybersecurity? That's what this annual security prediction roundup will cover, from the perspective of the top cybersecurity industry companies, thought leaders, executives and journalists. Every year we catalogue the evaluators to see who has made a New Year's security prediction list and checked it twice.

Technological disruption is at the peak with many promising artificial intelligence projects surfacing in 2019. So, it's time that entrepreneurs consider this to be a matter of grave concern and shift their focus from counting profits to enhancing business processes in order to count on customer experience. Ok, this might sound so little vague. As digital transformation includes multiple technologies and it is not easy for any to embed all. Hence, to stay at the forefront we will start with one technology that encapsulates all the present-day technological transitions.

From real-time diagnoses aided by machine learning to wearable devices that track and transmit patient data from a distance, a host of new and evolving technologies are poised to influence care delivery in 2020. As intuitive tools intended to maintain good health, not to react to an existing illness, these investments are designed to reduce hospitalizations and related costs. "We're seeing a shift away from using technology to advance specialty care and high-tech medicine and a shift toward using technology to enable prevention and primary care," Dr. Felix Matthews, a managing director and physician leader at Deloitte, tells HealthTech. The continuing challenge for hospitals, he adds, is finding the right tools and level of investment to tackle risks and reach enough patients to justify the effort. Once the domain of early adopters, wearables are poised to help healthcare professionals collect a wealth of data from a widening and more diverse pool of users.