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AI in healthcare: the hype-free prognosis
AI’s transformative potential in healthcare is undeniable. Imagine being able to detect diseases or rifle through drug combinations at lightning speed with the help of a machine learning algorithm. Or the ability to deliver personalised, 24/7 care from chatbots trained on centuries of medical knowhow. Or freeing up time-pressed practitioners by automating manual tasks. It sounds incredible, but where does the hypothetical end and the practical begin?
With regulatory, privacy, integration and security concerns baked into MedTech, healthcare, and pharma at molecular level, AI medical applications face an uphill battle if we’re to bring them to fruition.
In our unique, expert-driven whitepaper, "Incremental adoption: a holistic analysis of AI’s future in healthcare", we’ll explore exactly what that struggle will look like in real terms.
By carefully pulling healthcare technology innovation apart, we explore AI’s potential, its pitfalls, and possible workarounds to the sector’s biggest challenges.
And, ultimately, we provide our view on the road the industry must travel to make sustainable, secure, and ethical AI in healthcare a reality.
Finding a path through AI healthcare challenges
There’s no one-size-fits-all approach to AI adoption in healthcare, but our AI healthcare whitepaper offers healthcare leaders, practitioners, and policymakers a nuanced understanding of this powerful technology's opportunities and limitations. We provide a comprehensive overview of AI’s current role in healthcare and address pressing questions like:
- What are AI’s most promising applications in healthcare?
- Which fundamental challenges must be addressed?
- How can we ensure AI doesn’t replace human expertise?
- Which foundational next steps are necessary?
A look at the details
Uncover the shifting role of humans in healthcare
AI adoption in healthcare is going to change how people work, the nature of their roles, and the expected level of technological literacy. But will it replace people outright?
Sort the signal from the noise. The answer here is nuanced, but ultimately positions people as the future bastions of ethical, safe AI use.
Learn how to build with data quality and equity
How do you ensure that AI models are explainable, trustworthy, and representative of every type of patient?
Understand why fresh methodologies for data integrity need to be at the forefront of any AI application’s development.
Plot a roadmap for integrated, scalable AI implementation
How do you integrate pioneering technology into siloed, outdated architecture? And how can you do so in a way that scales?
Learn why data ecosystem management needs interoperability, robust frameworks, and a ‘pilot project’ approach to ensure success.
Global thinking. Expert opinions. Ratified strategies.
This whitepaper represents the opinions of a diverse pool of global experts in AI, healthcare, pharma, and MedTech, as well as external research into the pilots and projects already underway.
Through an exhaustive series of in-depth interviews, we’ve collated insights from some of the world’s leading minds at the intersection of artificial intelligence and healthcare.
Alongside our own decades-strong expertise in data strategy and innovation, the full whitepaper distils qualitative and quantitative research into a comprehensive audit of the technology’s potential, challenges, and possible future.
The goal? To rigorously stress-test the hype surrounding AI’s healthcare potentials – and provide a pragmatic, realistic strategy for AI implementation.
What's the smallest use case with a testable answer? There may be a big addressable market, but starting with proof of functionality is crucial.
– Data Science Director large European healthcare company
Download the whitepaper
Deep dive into the core AI healthcare challenges – and how to overcome them – by downloading the free whitepaper in full: "Incremental adoption: a holistic analysis of AI’s future in healthcare".