These are perhaps the most powerful and important four words a woman can hear after a breast-screening visit. X-ray based mammography is an effective screening tool for detecting cancer, but what many women may not know is that breast screening programs produce a high level of false positive results, particularly after multiple years of screening. In other words, women are informed they may have cancer when in fact they don't. This is particularly true in the US, where each study is generally read by a single, expert radiologist. In Europe, two independent radiologists read each study.

Aidoc, a Tel-Aviv, Israel-based medical imaging company, announced back in August that it had gained FDA clearance for a new solution that helps radiologists triage patients using artificial intelligence (AI). Now, to meet an increase in customer demand as a result of that announcement, the company has hired Tom Shearer to manage sales in North America and Jeremy De Sy to handle sales throughout Europe. "AI isn't the future for medical imaging; it's the present," Shearer said in a prepared statement. "Aidoc is led by extraordinary individuals who have developed a revolutionary product. This solution is always running in the background, on every exam, filling a critical need in medical imaging by helping radiologists manage their increasing workload while maintaining high standards."

Artificial intelligence (AI) is becoming more common for screening, diagnosing and helping treat eye conditions. The technology already is used in online search engines, speech recognition tools and other smart devices. Now, AI is showing promise in healthcare. Massive amounts of data and growing computing power are fueling these advanced, algorithm-based technologies. Several studies show the potential for AI to help doctors detect eye disease.

That's how quickly brain damage happen when the cells get no oxygen in a stroke or in some brain injuries. Both can have tragic consequences -- paralysis, memory loss, speech difficulties and even death. But doctors can't start treatment without an initial diagnosis, and that requires reading a CT scan as soon as the test's completed. Unfortunately, that's not what usually happens, said Prashant Warier, co-founder of Qure.ai, a member of our Inception startup accelerator program. "Radiologists typically have a backlog of cases," he said.

The total global revenue opportunity for the healthcare artificial intelligence market will exceed $34 billion by 2025, according to a report from Tractica. The report notes that global software revenue from 22 key healthcare AI use cases will grow from $511.7 million in 2018 to $8.6 billion annually by 2025. More articles on artificial intelligence: Director of analytics tops list of top-paying AI jobs Indiana U School of Medicine partners with Fujifilm for AI research Dr. Eric Topol turns critical eye on landmark FDA-approved AI device

There is a significant difference between automation and the use of artificial intelligence (AI) in the medtech space. Automation, within a healthcare setting, is defined as the use of hardware and software specifically programmed to save time. AI can be categorized as machine learning, meaning software and hardware working in conjunction to effectively mimic human decision-making -- just much, much faster. AI can learn outside of its programming, and the goal is for the software to make a decision of equivalent quality, compared to a human. The use of automation and AI is integral within the medtech space, as data is becoming increasingly important to manage and understand.

Big pharma is taking an AI-first approach. Apple is revolutionizing clinical studies. We look at the top artificial intelligence trends reshaping healthcare. Healthcare is emerging as a prominent area for AI research and applications. And nearly every area across the industry will be impacted by the technology's rise. Image recognition, for example, is revolutionizing diagnostics. Recently, Google DeepMind's neural networks matched the accuracy of medical experts in diagnosing 50 sight-threatening eye diseases. Even pharma companies are experimenting with deep learning to design new drugs. For example, Merck partnered with startup Atomwise and GlaxoSmithKline is partnering with Insilico Medicine.

We've come a long way since the term artificial intelligence (AI) was coined by AI luminary John McCarthy at Dartmouth in 1955. Sixty-three years later, AI is transforming healthcare, fintech, and other industries across the spectrum. While the quest for a truly humanlike AI continues, advancements in big data and machine learning (ML) have helped AI go mainstream. According to Accenture, the U.S. AI healthcare market is projected to reach $6.6 billion by 2021--a compound annual growth rate (CAGR) of 40 percent. Medical imaging and diagnostic companies are fueling much of AI's growth in health tech. For example, Arterys, a cloud-based AI assistant for radiologists, received FDA clearance for analyzing images of lung and liver tumors with its Oncology AI suite in February 2018.

The first artificial intelligence (AI) diagnostic system to gain clearance from the U.S. Food and Drug Administration beat out all predetermined benchmarks, achieving "high diagnostic accuracy" for patients with certain forms of diabetic retinopathy, according to clinical trial findings. IDx, the developer of the system, IDx-DR, published its results this week in the peer-reviewed journal Nature Digital Medicine. The paper provides an inside look into a technology that could transform how the industry diagnoses diabetic retinopathy, a condition that can cause blindness, bringing the process from the specialist's office to primary care -- without the need for a clinician to interpret the results. READ: First-of-Its-Kind AI Tool for Diabetic Retinopathy Detection Approved by FDA "This is formerly uncharted territory in healthcare, making it especially critical that we ensure the highest level of safety before introducing autonomous AI into patient care," Michael D. Abràmoff, M.D., Ph.D., IDx's founder and president and the study's principal investigator, said in a statement. In April, the FDA cleared IDx-DR, which analyzes images of the eye, for detection of "more than mild" diabetic retinopathy in adults with diabetes.

The first FDA-approved AI system for diagnosing eye diseases caused by diabetes is completely autonomous, and doesn't require a doctor to interpret the results. Several corporations including Google and DeepMind have been working on building algorithms for diabetic retinography, a leading cause of blindness amongst adults. The first biz to release a device approved by the US Food and Drug Administration (FDA) earlier this year in April, however, is less well-known. IDx LLC, an AI diagnostics company based in Iowa, developed the tool known as IDx-DR. The details about the system were published in a paper in Nature Digital Medicine on Tuesday.