Have you ever seen (or eaten) a delicious meal and wished you had the recipe to make it? Now all you have to do is take a picture and give it to an algorithm developed by MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). Their algorithm can find a recipe for you based on nothing more than a single picture of the finished product. The researchers built their algorithm by combing through over a million different recipes collected from various recipe websites. They combined this recipe encyclopedia with image recognition software to identify the type of food in a photo and match it with its corresponding recipe.
An analytics tool developed by the Department of Defence's science and technology branch to guard against bioterrorism has found a new home in public health, thanks to a collaboration between its creators and Victoria's health department. EpiDefend is an algorithm created by Defence scientist Tony Lau and his team. It uses a'particle filtering' technique of statistical analysis to crunch through historical data on lab-confirmed flu cases, anonymised patient data from GPs, and collections of environmental data records to predict the spread of naturally occuring influenza. Up until now it has been used to identify organic disease outbreaks in order to differentiate them from more sinister causes, such as maliciously distributed viruses or bioterrorism. But the Defence team has now stumbled onto a mutually beneficial partnership with Victorian health authorities, who want to use EpiDefend ahead of next year's flu season to predict when and where influenza will break out, and to target their resources accordingly.
Ottawa researchers are taking a page from Netflix and Google to help patients, their families and their doctors have informed conversations about death. Researchers at Ottawa's newly minted National Centre for Individualized Health have developed an algorithm that predicts how many months, or years, patients near the ends of their lives have to live. It is information some people might not be comfortable with, acknowledged Dr. Peter Tanuseputro, an investigator at the Bruyère Research Institute and family doctor who offers house calls to his palliative patients. But he believes many elderly patients will want to know exactly how long they have to live, information not currently available for most. He also said everyone deserves access to the information, based on an individual's health information and data collected across Ontario.
Highlighting the company's rapid progress in the radiology space, Israeli startup Aidoc has received its third FDA clearance for its AI-based algorithm to help highlight potential instances of cervical spinal fractures. The regulatory decision comes just a few weeks after the FDA cleared the company's pulmonary embolism product. Aidoc also has approval for its algorithm for the detection of intracranial hemorrhages through CT scans. The company's cervical spinal fracture product already received approval from European regulators. Delayed diagnosis of cervical spinal fracture is a common problem in emergency rooms and can lead to potential major neurological issues including quadriplegia.
The creation of narrow artificial intelligence which performs better than humans on specific tasks raises a host of ethical issues. Clearly, it is important to ensure that the algorithms do not harm humans. As AI algorithms start to play an increasingly large role in future healthcare systems, taking on cognitive work with social dimensions it will become increasingly important to develop AI algorithms that are not just powerful and scalable, but also transparent and open to inspection--to point out just one of many socially important properties. This morning I attended a breakfast meeting organized by a federal organisation which represents the German Digital Economy (BVDW). Wolfgang Gründinger--a talented author, analyst and lobbyist for the Digital Transformation--invited a diverse group to discuss digital ethics.