Works on the use of algorithms, based on artificial intelligence, has been predicting the possibility of a pandemic for many years, whilst models developed by researchers have been used effectively in the fight against infectious diseases, thus limiting their development. An example of such activity are the achievements of AIME company (Artificial Intelligence and Medical Epidemiology), which since 2012 has been conducting research on the possibilities of using AI to predict the course of infectious disease epidemics. In 2017, the models, trained on a huge amount of data, reached 86% effectiveness in predicting the locations where the Zika and dengue virus outbreaks occurred within the following three months. Bill Gates TED Talk in 2015 is known primarily among people who consider the COVID-19 a global conspiracy. In fact, it is impossible not to notice similarities between the course of the current epidemic and the hypothetical super-virus pandemic described by Gates in his speech.
A simple eye exam combined with powerful artificial intelligence (AI) machine learning technology could provide early detection of Parkinson's disease, according to research being presented at the annual meeting of the Radiological Society of North America (RSNA). Parkinson's disease is a progressive disorder of the central nervous system that affects millions of people worldwide. Diagnosis is typically based on symptoms like tremors, muscle stiffness and impaired balance--an approach that has significant limitations. "The issue with that method is that patients usually develop symptoms only after prolonged progression with significant injury to dopamine brain neurons," said study lead author Maximillian Diaz, a biomedical engineering Ph.D. student at the University of Florida in Gainesville, Florida. "This means that we are diagnosing patients late in the disease process." Disease progression is characterized by nerve cell decay that thins the walls of the retina, the layer of tissue that lines the back of the eyeball.
In today's world of fast fashion, retailers sell only a fraction of their inventory, and consumers keep their clothes for about half as long as they did 15 years ago. As a result, the clothing industry has become associated with swelling greenhouse gas emissions and wasteful practices. The startup Armoire is addressing these issues with a clothing rental service designed to increase the utilization of clothes and save customers time. The service is based on machine-learning algorithms that use feedback from users to make better predictions about what they'll wear. Customers pay a flat monthly price to get access to a range of high-end styles.
Medical imaging is the process of capturing the structure of an inner organ or tissue. These images can assist medical staff with diagnostics, treatment, and monitoring of patients. It can also prevent any unnecessary invasive procedures. The global AI healthcare market is expected to grow from 4.9 billion USD in 2020 to 45.2 billion USD by 2026. This rapid growth rate can be explained by the many advantages AI has to offer.
BEGIN ARTICLE PREVIEW: The automotive sector has, for years, driven the growth of the robotics industry. But robots are now moving beyond industrial manufacturing environments and into other industries, including agriculture, construction, healthcare and logistics, to name a few. As robots continue to find new applications, alleviating concerns about safety and security are crucial to their adoption, acceptance and success. Thanks in part to the COVID-19 pandemic, many workplaces will in the near future see new robots working alongside their human coworkers. Safety and security must be top of mind as robots can bring risks, and security threats can become safety threats. Constant Internet connectivity is often required for many robots to get software updates or to send and receive data. This connectivity leads to new safety challenges and cyber attack opportunities, and robot designers, system architects, and end users need to consider the safety and security o
On this episode of Brains Behind AI, Ari and Natalie met with Bobby Palmer, the President and CEO of PotentiaMetrics, an Austin-based healthcare data and AI company. PotentiaMetrics' data analytics and artificial intelligence platforms help providers, payers and medical technology companies inform personalized treatment plans by comparing patient-level outcome data related to survival, quality of life and cost of care. These companies use PotentiaMetrics platforms to compare effectiveness, adjust for risk, and track outcomes-based performance metrics. Bobby has been a business owner and CEO for over 20 years, creating the vision and strategic direction to develop multi-institutional, real-world outcomes registries that enable the creation of unique and personalized AI platforms. Bobby received his MBA from Washington University in St. Louis.
It's been a decade since construction players began embracing digital solutions. In the early- to mid-2010s, thousands of new market entrants offered point solutions that served existing use cases or, in some instances, created new ones. The first widely adopted construction point solutions addressed basic needs; for example, improving design capabilities or digitizing paper-based information. By the second half of the decade, industry players--spurred by end-customer feedback about their difficulty integrating point solutions--began expanding their product portfolios to create suites of integrated solutions. While the construction technology industry is still filled with players offering point solutions or limited suites, our latest annual effort to map and understand the construction technology landscape reveals that the industry is moving toward platforms and predicts that a combination of multiple platforms will coexist in the space.