In the healthcare industry, data science and artificial intelligence (AI) play a pivotal role in bringing together innovation and patient care and they have the potential to transform how healthcare is delivered. Healthcare data open the road to many discoveries. For example, it provides the foundation to run medical evaluation and to produce more effective drugs more quickly. Data scientists are using powerful predictive analytical tools to detect chronic diseases at an early level and to identify successful interventions quickly. Analytical tools will make possible to identify more quickly the best drug for a certain treatment as well as the most efficient route to produce it.

The COVID-19 pandemic has supercharged the scope of the issues the global healthcare industry was already grappling with. When the pandemic arrived, healthcare organisations often struggled to find the basic information they needed to respond -- whether it was disease and death rates or the availability of hospital beds and critical supplies. Among other problems, the pandemic highlighted the desperate need for collaborative data analytics in healthcare. As McKinsey observed, healthcare's digital barriers are often decidedly non-technological. The technology is out there (or rapidly evolving) -- in October 2020, Pfizer and IBM researchers announced that they have developed a machine learning technique that can predict Alzheimer's disease years before symptoms develop.

The British Embassy in Israel launched it's flagship technology program - TeXchange 2020 - which this year will focus on healthcare innovation. The Embassy is inviting Israeli startups to apply for a program that one of its alumni has described as "a lifetime membership to the UK government and key players." TeXchange is the annual flagship program of the UK Israel Tech Hub, and has been running successfully since 2012. Every year, the Hub focuses on a different sector. "The program creates an ongoing two-way flow of digital tech pioneers, companies, ideas and technology between the UK and Israel," the TeXchange team explained, "and it creates platforms for collaboration between entrepreneurs and companies, connecting Israeli startups to the UK's leading companies, markets, investors and service providers while giving British corporations a competitive advantage by integrating Israeli technological innovation into their business."

The Entrepreneurship Centre at Cambridge Judge supports new programme that uses artificial intelligence to tackle major NHS challenges. The Entrepreneurship Centre at Cambridge Judge Business School and the Eastern Academic Health Science Network (Eastern AHSN) are sponsoring a new programme that brings together the health sector, universities and the tech industry to use artificial intelligence to tackle major challenges in the National Health Service. Applications are now open for the programme, called MedTechBOOST, which has been launched by business network Central Working and innovation specialists Studio Zao. The five day, free-to-enter programme starts on 2 September 2019 at The Bradfield Centre, the tech hub at Cambridge Science Park. It is open to startups, technologists, researchers, PhDs, consultants and other clinicians who would like the opportunity to come together with supporters and partners to co-create solutions that address two of the biggest challenges facing the NHS today – mental health and healthy ageing.

AI, design thinking, robotics and big data have made a splash across all industries, but perhaps their greatest impact is in healthcare. As technology and innovation have grown in the healthcare field, hospitals and startups have found amazing ways to improve their offerings and revolutionize the industry. The result is amazing applications of new technology and thinking that can forever change how patients are treated. Here are 10 examples of explosive innovative in healthcare. Pennsylvania Hospital is steeped in history, but a new facility will bring in new thinking and technology.

We live in an era of astounding healthcare innovation. Within living memory, we've seen the first cardiac pacemaker implanted and the first successful heart transplant. Measles, mumps, rubella, and chickenpox were, for all intents and purposes, eradicated in the US through public health vaccination campaigns. And, the human genome has been fully-sequenced. The net result of all this innovation is longer life spans worldwide, going from an expected life span of 48 years in 1950 to 71.5 years in 2014. Much of today's healthcare innovation is focused on technological advances.

It's a common nightmare for programmers to come in late to a project or organization and then have to make sense of a complex "spaghetti mess" of code created over the previous 10 years -- a technical debt that takes huge resources in time and money to clean up. Ten years of technical debt is an all-too common headache: Decades of debt were at the root of the Y2K COBOL nightmare. MySpace struggled famously for years with a crippling tower of technical debt. And today, both fast-growing startups and long-standing companies have to deal with legacy code on an ongoing basis in their engineering organizations and beyond. But none of this compares to the billions of years of "technical debt" in biology.

When we asked dozens of venture capitalists where they see the most potential for applied artificial intelligence, they unanimously agreed on healthcare. Technology has already been used to incrementally improve patient medical records, care delivery, diagnostic accuracy, and drug development, but with A.I. we could achieve exponential breakthroughs. Deep learning first caught the media's attention when a team from the lab of Geoffrey Hinton at the University of Toronto won a Merck drug discovery competition despite having no experience with molecular biology and pharmaceutical development. Recently, a multidisciplinary research team at Stanford's School of Medicine comprised of pathologists, biomedical engineers, geneticists, and computer scientists developed deep learning algorithms that diagnose lung cancer more accurately than human pathologists. The ultimate dream in healthcare is to eradicate disease entirely.

But is the Big Data movement going to make a difference? I'm strongly in favor of cognition, computing, and computing that is smarter rather than dumber. But is the Cognitive Computing movement likely to make a difference?