A group of doctors and data scientists is calling on hospitals to create clinical departments devoted to artificial intelligence to harness the power of the technology to transform patient care. While there have been many predictions of AI's potential to benefit health care delivery -- from helping doctors perform surgery to catching cancer earlier -- the technology's benefits so far have been blunted by inconsistent implementation, the researchers say. They outline a plan to make hospitals "AI ready," in a way they say would enhance both patient care and medical research. UVA Health's Dr. David J. Stone and colleagues from several other major medical centers outline their plan in "The Clinical Artificial Intelligence Department: A Prerequisite for Success," published in BMJ Health & Care Informatics. They begin by offering a frank assessment of the current integration of AI in health care: "The reality of the available evidence increasingly leaves little room for optimism," they write.
EPSRC, on behalf of UKRI, is delivering this substantive phase of the Turing Artificial Intelligence (AI) Fellowships, working in partnership with The Alan Turing Institute, Department for Business, Energy and Industrial Strategy (BEIS) and the Office for Artificial Intelligence. Through this programme we aim to grow the UK's capability and capacity in addressing the methodological and theoretical challenges in AI and enable enhanced engagement between academia, industry and other sectors through flexible career paths that encourage inter-sector mobility. Outline proposals are invited for the Turing AI Acceleration Fellowships call. Up to £18 million is available to fund 10-15 fellows for 5 years. We are seeking to invest in the next generation of AI researchers who will undertake ambitious and novel research with a primary focus on tackling the methodological and theoretical challenges in AI driven by real world applications.
UCLA collaborated with Amazon to launch a center for artificial intelligence research, education and outreach Oct. 29. The Science Hub for Humanity and Artificial Intelligence, based at the UCLA Henry Samueli School of Engineering and Applied Science, aims to address social issues and create positive impacts using artificial intelligence. The three main focuses of the Science Hub are combining research efforts, funding doctoral fellowships and continuing community outreach, as stated on the website. According to the UCLA press release, this is Amazon's first collaboration with a public university. UCLA received $1 million from Amazon to establish the hub this year, and the agreement may be renewed for a maximum of four more years.
Fifteen UK researchers have been awarded the Fellowships, named after AI pioneer Alan Turing, supported by a £20million government investment. As a result of the government investment, Fellows will work with academia and industry to help elevate their world-class research and transfer their innovations from the lab to the real world. These innovations have the potential to change how people live, work and communicate, helping to place the UK at the forefront of the AI and data revolution. Dr Hernandez Lobato's research focus will be on'Machine Learning for Molecular Design'. Many existing challenges, from personalised health care to energy production and storage, require the design and manufacture of new molecules.
MIT's School of Engineering and Takeda Pharmaceuticals Company are working together to drive innovation and application of new artificial intelligence applications for healthcare and drug development. WHY IT MATTERS The program, based at MIT's Abdul Latif Jameel Clinic for Machine Learning in Health, or J-Clinic – which specializes in developing new healthcare AI tools – is funded with a three-year investment from Takeda and aims to leverage the expertise of both organizations. With the collaboration, MIT will gain access to pharmaceutical infrastructure and expertise, and develop new educational program through J-Clinic that will support MIT faculty, students, researchers, and staff in their approach to AI development. The new program will combine algorithm and hardware innovations, and create multidimensional collaborations between academia and industry. THE LARGER TREND The MIT-Takeda Program will focus on funding as many as 10 flagship research projects per year in the areas of machine learning and health,including diagnosis of disease, prediction of treatment response, development of novel biomarkers, process control and improvement, drug discovery, and clinical trial optimization.