The thought of a ransomware attack on your hospital or health system may keep you up at night.

Healthcare system survival pivots on many metrics, but the ability to generate revenue and to evidence high quality of care are two of the most essential. At the center of both metrics is the clinical documentation process, where an accurate representation of every patient's clinical experience while in a provider's care must be recorded. As simple as it may sound, achieving that accurate reflection of diagnoses, interventions and the clinical picture is anything but simple. Medicine is as much science as it is art, and complex definitions, levels of specificity and complex medical terminology mean that most hospitals struggle to document everything properly, leading to significant lost revenues and under-reporting on quality metrics. Health systems have answered this challenge by standing up clinical documentation integrity (CDI) programs, staffed with clinicians.

Qualcomm just announced its latest premium mobile processor, the Snapdragon 888. This 5 nm chip, rumored to be made at a Samsung facility, provides multiple levels of improvement in central processing power, high end graphics that approach the capabilities of a gaming console. There are also camera improvements that threaten stand-alone DSLR, and AI functions that enhance and protect camera still and video images from "Deep Fakes" while also providing big improvements in AI inference workloads. And, of course, it runs on 5G networks, along with supporting faster Wi-Fi 6 and 6E capability. One feature that stands out for me seems to be buried in most coverage of the 888 processor and has the potential for dramatically changing the way mobile devices work, as well as enhancing security well beyond where we are today.

My views are similar to Jenny's here. It also depends what you mean by AI as it's a rather hyped term and I have sat in a meeting and heard someone describe it as'superior intelligence', which it is not. Machine learning and algorithms might be more appropriate descriptions and here the challenge is transparency and trust. We need to be confident that ultimately there is a clinician making an informed judgement in a patients best interest. That requires oversight as well as understanding how the algorithm works, the decision tree and the dataset used to develop/train the algorithms. The other element is data security and this is something that patients themselves have raised.

Artificial intelligence is already changing medicine across many specialties, and in gastroenterology, new AI developments are coming online at breakneck speed. AI protocols and devices are being created and refined so they can identify abnormalities in a colonoscopy, diagnose disease, predict outcomes, and assist with treatment. With some already in use and others with potential to come into practice in the next one to five years, the opportunities are endless for how AI can contribute to better, more efficient patient care. Research has shown that after being "trained" through machine learning with thousands of photos and videos from actual colonoscopies, a computer-assisted diagnosis system can accurately spot and diagnose abnormalities during colonoscopy. When refined and adopted, this technology could increase a skilled endoscopists' speed and effectiveness.

Few ideas in the last decade have provoked as much excitement, or as much confusion, as the introduction of artificial intelligence (AI) in oncology. From the first moment we announced our plans to apply our Watson technology to help oncologists, we were met with a stark dichotomy of emotion. The headlines ran the spectrum from hype (your next doctor might be a robot!) to cynicism (5 reasons AI in healthcare will fail). Today, five years into the journey to help improve cancer treatment through data, analytics and AI, while we're still very much in the early stages, I'm happy to report that the real-world progress is far more encouraging than either of those early storylines would suggest. In fact, not only is AI being used to support physicians in the delivery of cancer care today, it is producing quantifiable results while charting a course for the future.

The growth of artificial intelligence in the healthcare industry has been astounding. Each day, we see new articles about AI-related advances in medical imaging, diagnosis, and health informatics. Health service providers are finding more and more ways to match patients with treatment options, improve the detection of disease, and analyze patients' data to give them more insight into their individual health profiles. AI is also used to improve clinical payment structures, develop treatment plans, and optimize coordination between clinical staff. The U.S. patent system--a key player in protecting R&D innovation--is also experiencing tremendous growth, with patent filings for AI-related technologies trending upward.

We are witnessing just the beginning of the artificial intelligence (AI) era. The computer program AlphaGo defeated the world's top player in the complex Chinese board game of Go for the last time in May 2017. The program had run out of human competition. Instead, its developers designed AlphaGo Zero to simply play against itself without the aid of any historical game data. AlphaGo Zero taught itself how to beat all versions of AlphaGo in 40 days.