Artificial intelligence (AI) has been the dominant topic in medicine and healthcare for years as these fields have become more and more technology-dependent. Then, in November 2022, generative AI stormed onto the scene and captured the attention of the masses.
The release of ChatGPT finally meant that AI was not a tool for a handful of developers and researchers, but millions of people could start using it in practice. Our latest ebook covers this technological revolution.
From the onset, we at The Medical Futurist have been diligently covering all news, studies, and announcements to help patients, healthcare professionals, company leaders and policymakers better understand what generative AI can bring to their lives and jobs, without overhyping or understating its importance.
We hope that this e-book will further serve that goal and provide a clear picture of what we all can expect from this breakthrough technology. Let’s have no doubts: the coming years will be as impactful as when the Internet started its worldwide journey. We will remain at your disposal to get the context in the mess of news and press releases.
What can you expect from this book?
We had several goals in mind when we started writing this book.
The first was to set expectations right. Interestingly, we have actually not made major breakthroughs in AI development in the past few months, although with the advent of ChatGPT, the topic suddenly garnered immense attention. Along with this media hype, we were inundated with extreme views. They covered the entire conceivable spectrum from ‘doomsday prophets’ declaring the end of humanity to utopian dreamers anticipating a miraculous AI that solves all of humanity’s problems.
Let’s be clear: this IS a technological revolution. And as such, it brings major opportunities and major challenges. Being paralysed with fear or blindly believing in miracles will not help us make the most (and best) of it.
Our aim was not only to provide you with a general understanding of the topic but also to equip you with a working knowledge of these new technologies that you can easily grasp and utilize. This working knowledge will in turn help you to become better in what you do.
What’s in the book?
We’ll embark on this journey in four chapters:
- What is generative AI and why do we care about it? From the basic terms and definitions to everyday use cases, we get to know this field, and also clarify what these tools are capable of and what’s over their capabilities. We explain why their IQ is zero and how these tools can be so useful and clever without being creative in the human sense of the term and without a conceptual understanding of its topics.
- Large language models (LLMs), the most popular generative AI tools. Once we’ve charted the terrain and the risks, we dive into the legitimate reasons for the current generative AI hype. We delve deeper into how it can benefit the healthcare sector, patients, and healthcare professionals, and we separate the realistic possibilities from the no-gos.
- The evolution of LLMs. We’ll venture into what the generative AI future holds, how it will develop, and what will be the implications of these developments for the world of medicine.
- What’s next? A glimpse into the AI-laced healthcare future. In the final chapter, we dissect how we can best utilize the AI revolution, enumerating the necessary steps on all fronts of the medical spectrum. This ranges from individual preparations to regulatory requirements, from the changes necessary in medical education to the actions businesses need to take. We analyze risks and potential pitfalls and enumerate reasons for optimism. And we wrap up the book with a checklist to help you decide if you are prepared for the AI-healthcare future.
3 things you should expect from generative AI
Addressing Medical Shortages
The world is increasingly faced with a shortage of healthcare professionals, a scenario made even more challenging as life expectancy grows and chronic conditions are more efficiently managed. Enter large language models developed specifically for medical use, like Google’s Med-PaLM. These AI models are poised to become the new frontier for first contact in healthcare systems. As waiting times to consult a human specialist stretch into days or weeks due to access barriers and capacity shortages, the prospect of seeking initial consultations from these AI models is becoming a safer option.
Eventually, these AI tools will capably handle straightforward cases, leaving the more complex ones to human healthcare specialists. This reallocation not only improves efficiency but also allows human experts to focus on the tasks that truly need their expertise. In a world where a medical professional’s time is a luxury, this shift provides a promising solution to prevent human capacities from being wasted on mundane, time-consuming activities.
Generative AI made artificial intelligence an everyday reality for doctors and patients alike
In November 2022, OpenAI publicly launched its large language model ChatGPT. It reached the milestone of having over 100 million users in only 2 months. In comparison, reaching the same milestone took TikTok and Instagram 9 months and more than 2 years, respectively.
LLMs have initiated a wave of products and services using generative artificial intelligence (AI), which had previously found it hard to attract physicians. No matter how many studies, clinical trials, regulatory approvals, and product announcements kept on becoming available about AI’s role in medicine and health care, adoption rates have been lagging behind. One of the reasons for this has been limited access to AI technologies. There have been hundreds of AI applications with regulatory approval; however, they were only available in limited healthcare institutions to a select group of physicians.
Since the end of 2022, basic AI tools and services using generative AI have become widely accessible. This might mark the beginning of AI becoming used in practice by the average medical professional (and patient). AI stepped out of the shadows where it only mingled with senior data scientists and nerdy professors and became available for everyone.
The future is multimodal
Indisputably, the future of generative AI is multimodal – this means that LLMs will quickly evolve to work with all kinds of prompts, not just text. Many models – although not yet publicly available – are already reported to encompass a range of input types, including images, sounds, handwritten notes and more complex behavioral data. In the medical field, this means a future where AI can analyse a patient’s health holistically, from medical records and lab results to visual data such as scans and MRIs, the doctors’ notes and even auditory data from patient interactions.
Step into the future and discover how generative AI is not just an innovation but a revolution in healthcare. Equip yourself with the knowledge to be at the forefront of this change. Secure your copy today and be part of the next big leap in medical science!
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