Earlier this year, consulting firm Frost & Sullivan predicted that artificial intelligence in healthcare will see a "dramatic market expansion" in the next couple of years, with the potential to reduce the cost of medical treatments by half across the board. "By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries," said Harpreet Singh Buttar, an analyst at Frost & Sullivan. With this in mind, we identified 32 companies that are already applying machine learning techniques and predictive analytics to reduce drug discovery times, provide virtual assistance to patients, and diagnose ailments by processing medical images, among other things. The 32 startups on the list have raised more than 530M in aggregate funding. This year, New York-based AiCure raised 12.3M in Series A funding and National Science Foundation-grantee Cloud Pharmaceuticals raised a 350K round from undisclosed investors.
How much can a 17-year-old boy really know about women? For starters, that thousands face heartbreaking and costly misdiagnosed breast cancer scares every year. Abu Qader, who's about to start his final year in the Chicago public school system's Lane Technical College Prep High School, was born in war-scarred Afghanistan but has spent most of his 17 years on Earth in the U.S. Qader and European business partner Vedad Mesanovic, who focuses on young and under-resourced scientists, created a company they call GliaLab (named after the cells that support and protect neurons). They are now courting venture capitalists for a targeted 600,000 to help finance the breast cancer-focused artificial intelligence that Qader first created for a 10th-grade class project. Qader believes his technology can help women (and men, too) take on potentially deadly breast tumors and non-cancerous growths by using the convenience of their own mobile phone or tablet to aid in diagnosis and classification, reduce human error and save the expense of false-positive readings.
You don't need to be a chemist to make triacetone triperoxide, or TATP, the homemade explosive used in the bombs which killed 35 people and injured hundreds more last week in Brussels, according to one expert. Another calls the process "worryingly easy." The recipe can be found on the Internet, the ingredients -- hydrogen peroxide and acetone -- can be found at any drugstore, and can be mixed using regular kitchen equipment. "For the most part, IED components are commercial goods that are not subject to government export licences and whose transfer is far less scrutinised and regulated than the transfer of weapons," said a February report from the London-based Conflict Armament Research group, which traced the origins of more than 700 components recovered from ISIS bomb factories. In an attempt to head off attacks like those in Brussels, Boston, and scores of other places, the United States government has quietly asked the general public -- from credentialed professionals to "skilled hobbyists" -- to find ways of weaponizing "easily purchased, relatively benign technologies."
You don't have to be a gambler to appreciate the complexities of the card game Texas Hold'Em. It involves a strategy that needs to evolve based on the players around the table, it takes a certain amount of intuition, and it doesn't require the player to win every hand. Just a few days ago, an artificial intelligence (AI) algorithm named Libratus beat four professional poker players at a no-limit Texas Hold'Em tournament played out over 20 days. If you have even the slightest understanding of how to write code, you would realize that it is impossible to actually code a software program to do that with such "imperfect information". The AI algorithm did exceptionally well and was utilizing strategies that humans had never used before.
Advances in clinical uses of artificial intelligence (AI) could have two profound effects on the global medical workforce. AI, which mimics cognitive functions such as learning and problem-solving, is already making inroads into the NHS. In north London it is piloting use of an app aimed at users of the non-emergency 111 service, while the Royal Free London NHS foundation trust has teamed up with Google's DeepMind AI arm to develop an app aimed at patients with signs of acute kidney injury. The hospital claims the project, which uses information from more than 1.6 million patients a year, could free up more than half a million hours annually spent on paperwork. AI raises the prospect of making affordable healthcare accessible to all.