Personalised Medicine Why the Pharmaceutical Industry Needs Automated Machine Learning While there are pharmaceutical drugs available to treat every type of ailment, the long drug development process creates massive obstacles for the industry, not to mention for those in need of treatment. Bringing...
Deep Learning Discover Examples of Practical Applications of Deep Learning Global experts in both industry and academia will once again come together at the Deep Learning Summit & Deep Learning in Healthcare Summit in Boston, 23 & 24 May, to explore the latest...
Healthcare Interview with Mark Gooding, Chief Scientist at Mirada Medical Medical imaging is widely regarded as one of the core components of the healthcare industry, it accounts for at least 90% of all medical data. The application of deep learning into medical imaging,...
Deep Learning How is AI transforming Bioinformatics? We live in a century where access to information is ubiquitous and change is the only constant. Artificial intelligence, once a futuristic concept, is now transforming industries globally. The development of cognitive computing...
Deep Learning Startup Series - Jon French, Next Canada Startup activity is critical to any technology or innovation ecosystem. Startups are often where the most disruptive ideas are hatched - ideas that impact industries and push the incumbent tech giants to stay...
Deep Learning Startup Series - Samir Kumar, M12, Microsoft's Venture Fund At each RE•WORK summit, we welcome a large variety of startups. With our key partners, we are taking a look at some of the most cutting-edge startups to watch out for.Startups...
Healthcare Creating a World Where Clinical Care is Data-Driven, Intelligent and Patient Focused This article is taken from the white paper 'Should You Be Using AI In Your Business?'. Download the complimentary paper here.Artificial Intelligence has the capacity to transform all aspects of healthcare...
Neural Networks Wearables, Algorithmic Fairness and Image Recognition: What You Missed at the Women in AI Dinner Last night at the Women in AI dinner in London, we brought together leading female minds working in AI to discuss algorithmic fairness, unused local computational opportunities, image recognition and other topics.The...
Deep Learning Insilico Medicine: Converging AI and Blockchain in Pharmaceuticals AI is transforming the healthcare industry and has the potential to disrupt and improve the way we discover drugs and will allow us to drastically improve the current methods of biomarker discovery. This...
Deep Learning Reflecting on the first half of 2017 Over the last 6 months, I have had the pleasure of being at most events and meeting some extraordinary people. As an intern, I have been exposed to so many more things than...
Machine Learning Using AI to Improve Quality of Life For Diabetic Patients The world of startups is constantly moving and evolving. With the exponential growth of deep learning research and technologies in recent years, innovative new companies are often funded, acquired and transformed from startups...
Deep Learning Cloud-based Deep Learning: Reducing Tedium in Radiology Radiology requires countless hours searching for tiny lesions, creating distance and contour annotations, and filling out checklists to determine stages of disease - these tasks are onerous and error-prone, resulting in high costs...
Deep Learning Addressing the Critical Issues of Deep Learning in Medical Imaging Since being named as one of the top 10 breakthrough technologies of 2013, deep learning has hit the headlines repeatedly, with new applications emerging rapidly. In particular, deep learning techniques have proven to...
Deep Learning "A Great Promise for Personalised Health" Last Tuesday, the Deep Learning in Healthcare Summit London took place at LSO St Luke’s.RE•WORK hosted 40 speakers and 200 attendees over the course of the 2-day summit to explore...
Big Data Opening the Black Box: Interpretable Deep Learning for Genomics Deep learning models are often noted as "black boxes" in reference to the difficulties of tracing a prediction back to important features to understand how an output was arrived at. Although deep learning...
Deep Learning Deep Learning at the Front Lines of Healthcare Today’s healthcare system was not built for a seamless integration of rapidly emerging technologies, such as machine learning innovations. Health data is largely inaccessible and not standardized, making it challenging to work...
Voice Recognition Bots in Healthcare: Will They Assist or Replace Humans? With the increasingly rapid technological advancements in natural language processing (NLP) and deep learning, development of virtual assistants and chatbots has exploded this year, and new applications are being explored everyday. One area...
Big Data Democratising Deep Learning: The Data Delusion Neil Lawrence is Senior Principal Scientist at Amazon, and Professor of Machine Learning at the University of Sheffield. His main technical research interest is machine learning through probabilistic models, with focuses on both...
Deep Learning Why Genomic Medicine Needs Deep Learning Brendan Frey is Co-founder and CEO of Deep Genomics, a company that aims to develop machine learning technologies to transform precision medicine, genetic testing, diagnostics and the development of therapies. His group has...
Big Data The Intersection of AI & IoT for a Healthier Smart Home There are countless connected home products available, but are they actually "smart"?Sean Lorenz, CEO & Founder of Senter, believes mainstream consumer adoption of connected home products will only happen when we begin...
Big Data Deep Learning in Healthcare Part 2: Future & Predictions View Part 1 of the discussion here. The application of artificial intelligence and deep learning in healthcare and medicine is often quoted to grow tenfold in 5 years, from algorithms that learn to...
Big Data Deep Learning in Healthcare Part 1: Opportunities & Risks The application of artificial intelligence and deep learning in healthcare and medicine is often quoted to grow tenfold in 5 years, from algorithms that learn to recognise complex patterns within rich medical data,...
