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10 Industries AI Will Disrupt the Most by 2030


Artificial intelligence, machine learning, and deep learning technologies have entered the mainstream; they are being adopted by enterprises all over the world. While these technologies certainly hold the potential to vastly improve the quality of operations in the corporate sector, they also stand to disrupt many existing markets. AI can easily be extended, adapted, and applied to different business operations. When considering that AI is just a computer program, we can begin to see the potential scope of the technology. The reason that AI is being adopted on such a large scale is due to its capacity to bring intelligence to tasks that previously did not have it. This, coupled with the technology's ability to automate repetitive processes with intelligence, makes it a highly disruptive power in various sectors. Keeping this in mind, we explored some of the industries that are most likely to be impacted by the widespread adoption of AI technology. Let us see why companies are so eager to adopt artificial intelligence.

The invisible warning signs that predict your future health


It was a sunny day outside, with a hint of spring in the air. I followed Angela, whose name has been changed to protect her identity, down the corridor towards my consulting room in Melbourne. She'd been my patient for several years, but that morning I noticed her shuffling her feet a little as she walked. Her facial expression seemed a bit flat and I noticed she had a mild tremor. I referred her to a neurologist and within a week she was commenced on treatment for Parkinson's disease, but I kicked myself for not picking up on her symptoms sooner.

Dr. AI: Challenges and Opportunities on the Road to AI-enabled Healthcare


Healthcare systems have evolved rapidly during the last decade and are now providing a variety of benefits to patients throughout the globe. This is because the healthcare industry has embraced artificial intelligence and is currently utilizing its many applications to provide a better and safer experience to patients suffering from different ailments. However, while discussing the benefits AI brings to the healthcare industry, one shouldn't forget that all that glitters in't gold. According to Bob Kocher, MD, an adjunct professor at the Stanford University School of Medicine, "if we are not careful, AI could…unintentionally exacerbate many of the worst aspects of our current healthcare system." This doesn't mean the advantages of AI should be ignored.

Top 10 Ways Artificial Intelligence is Impacting Healthcare


As the ability of artificial intelligence grows it is increasingly having an effect on many areas of our everyday lives. One area where is could have the biggest impact is artificial intelligence in healthcare. Smart technologies, machine learning programs and robotic devices are all contributing to the positive impact that artificial intelligence is having in the healthcare world. As technologies and our understanding of the possibilities provided by these technologies develops the impact of artificial intelligence in healthcare can only grow. What follows are 10 of the most important ways in which artificial intelligence is impacting positively on healthcare both now and in the future. For many years it has been possibly to obtain images of the insides of the human body through non-invasive means such as X-rays, CT scans and MRI scans. However many forms of diagnosis still require invasive action such as taking tissue samples or biopsies.

AI and medicine


For centuries, physicians and healers focused primarily on treating acute problems such as broken bones, wounds, and infections. "If you had an infectious disease, you went to the doctor, the doctor treated you, and then you went home," says Balaji Krishnapuram, director and distinguished engineer at IBM Watson Health. Today, the majority of healthcare revolves around treating chronic conditions such as heart disease, diabetes, and asthma. Treating chronic ailments often requires multiple visits to healthcare providers, over extended periods of time. In modern societies, "the old ways of delivering care will not work," says Krishnapuram. "We need to enable patients to take care of themselves to a far greater degree than before, and we need to move more treatment from the doctor's office or hospital to an outpatient setting or to the patient's home." Unlike traditional healthcare, which tends to be labor-intensive, emerging models of healthcare are knowledge-driven and data-intensive. Many of the newer healthcare delivery models will depend on a new generation of user-friendly, real-time big data analytics and artificial intelligence/machine learning (AI/ML) tools. Identifying risks, determining who is at risk, and identifying interventions that will reduce risk. Supporting and enabling customized self-care treatment plans for individual patients, monitoring patient health in real time, adjusting doses of medication, and providing incentives for behavioral changes leading to improved health. Optimizing healthcare processes (everything from medical treatment itself to the various ways insurers reimburse providers) through rigorous data analysis to improve outcomes and quality of care while reducing costs.