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When people set foolishly high goals, sensible people scoff. This is generally the right thing to do. However, sometimes it is worth considering the possibility that even the most surprising aspiration can be achieved.
In 2015, Priscilla ChanPediatrician, and her husband Mark Zuckerbergfounder of Facebookthey created chan zuckerberg initiative (czi) With the goal of helping science create a world in which all diseases can be prevented, cured, or controlled. As expected, company sentiment was technology-focused. But it wasn’t until 2020 that Chan-Zuckerberg’s annual updates began talking about the potential of artificial intelligence (AI). Four years later, it’s hard to imagine anyone achieving their goals without keeping their goals at the forefront.
The proportion of biomedical research articles invoking artificial intelligence was growing rapidly long before this field dazzled the world. “Basic Model” Such as various GPS (Pre-trained Generator Transformer). OpenAI, Meta Llama and Google Gemini, Given the large amounts of data produced by biomedical research, the early application of AI is not surprising. However, those advances and promises of the past are merely a prelude to what is going on now.
Artificial intelligence systems with the same power as basic models and large language models that generate compelling text in all kinds of genres, answer complex questions in fairly concrete and useful ways, and create images that represent ideas expressed in verbal signals. Catching up, becoming a part of health. Attention. They have applications for almost all parts. They can improve decisions made by researchers about how to edit genes; They are exceptionally good at making sense of big data from disparate sources; They can suggest new targets for drug development and help invent large and small molecules that can work as drugs against them. Czi himself is now working on the creation of a “virtual cell” powered by artificial intelligence with which he hopes to revolutionize all types of biomedical research.
The effects are not limited to the laboratory. Many of the types of diagnoses in which AI plays a role appear ripe for change. Robotic surgeons are performing an increasing number of operations. The way patients access health information and are motivated to adhere to treatment regimens is poised to be reinvented as chatbots and wearable health monitors learn to work together. The productivity of health care systems is likely to improve significantly.
Poor countries may benefit more. An older generation of AI is already making its presence felt there in healthcare. One advantage is that it can make a modest piece of equipment more capable, allowing it to be used more widely outside the clinic. Smart stethoscopes can help users detect key details, phones can become “tricorders” that measure heart rate, temperature, breathing and blood oxygen saturation at the same time. Providing reliable guidance to healthcare workers around the world in their native language represents a simple and revolutionary advancement.
If these tools can become widespread and if health care systems are reformed to take maximum advantage of them, they should provide better care. This represents an opportunity to improve the lives of hundreds of millions, even billions, of people.
Some see this as not only human progress, but epistemology: an entirely new kind of knowledge. Artificial intelligence can find associations and connections in disparate data sets that are too vast and confusing for humans to figure out which types of causes lead to which types of effects, without the need for pre-existing models. . Demis Hassabisone of the founders of deepmindThe company, now part of Google, an artificial intelligence powerhouse, believes the ability will change the way humans understand life.
More than half of the 1,500 health providers were founded in the last seven years.
There are warnings. The basic model powering “generative” applications like ChatGPT has serious shortcomings. Whether they call it hallucination, as researchers used to call it, or collusion, as they now prefer, they make things up. Like most AI, if you train them on bad or irregular data, the results will not be what they should be. If the data is biased, as health data often is (it is often hard to get good data on minorities, low-income groups, and marginalized populations), the results will not serve the population as a whole as they should. And there may be harm … in underrepresented groups. The “non-deterministic” nature of the models (they will not always respond in the same way to the same stimulus) creates philosophical and practical problems for those who regulate medical devices. Blood pressure monitors and thermometers reflect reality more directly.
None of this has stopped the market for health care products and services from growing rapidly. Large AI companies have expressed interest in purchasing health care experts; Healthcare companies are buying AI. Research and MarketsOne analyst firm estimates that in 2023 the healthcare world will spend about $13 billion on AI-related hardware (such as specialized processing chips and the devices that contain them) and software that analyze diagnostics, remote patient imaging and monitoring, and much more. Provides something. , He believes this figure will reach $47 billion by 2028. Analysts at CB Insights estimate that investors will move a whopping $31.5 billion in equity funding into health care-related AI between 2019 and 2022. More than half of the 1,500 health AI providers were founded in the past. , Seven Years.
The digitalization of healthcare has faced costly disappointments. But there is a real possibility that AI will live up to some of the expectations pinned on it. Simpler, more forgiving interfaces to handle data and help with time management should make AI-based systems more convenient than in years past for doctors, patients and healthcare providers. And health care systems urgently need increased productivity if they are to adapt and improve in a world of higher costs and aging populations. The shortage of health care workers is projected to reach approximately 10 million by 2030, which is approximately 15% of the entire existing global health care workforce. Artificial intelligence alone will not solve that problem. But this may help.
This report will look at four ways in which this help is likely to be provided. Doctors who make diagnoses are already provided with assistance, much-needed help given that 800,000 Americans die or become disabled each year because of poor medical decisions. Support is provided to patients who want to understand their symptoms or need help and motivation to stay healthy. AI research tools and data management help companies trying to develop new treatments more quickly and reliably. And helps the system as a whole.
Current health systems are severely limited by a lack of workers and knowledge. Artificial intelligence can provide vital assistance on both fronts; It may be that it can offer a transformative amount of it. Will that change mean that, by 2100, all diseases will be prevented, treated or controlled? Not in itself. But it’s making that egoistic goal more probable. The discussion about the impact of AI is filled with fear and trepidation, sometimes justifiably so. What it offers to health around the world represents a fundamental potential for good.
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