Have you ever wondered how long you will live? Or how long someone else will live? Well, thanks to artificial intelligence (AI), you might soon find out. Scientists have developed a new model of AI that can predict your time of death with high accuracy, trained on millions of humans.
The model, called Deep Neural Network (DNN), is a type of machine learning technique that uses neural networks to filter and learn from huge amounts of data. The researchers trained the DNN on the Electronic Health Records (EHR) of nearly 2 million adults and children admitted to either the Stanford Hospital or Lucile Packard Children’s hospital to predict their mortality in next three to 12 months.
The good news is that the DNN can do so with a precision of 90 percent. That means it can correctly identify 90 out of 100 patients who will die within the given time frame. The bad news is that it can also identify 10 out of 100 patients who will die prematurely, before they reach their expected life expectancy.
The researchers hope that this model can help improve palliative care for patients who are suffering from serious illnesses and may benefit from having end-of-life conversations earlier. Palliative care is a type of care that focuses on relieving pain and other symptoms, as well as providing emotional and spiritual support for patients and their families.
By using the DNN, palliative care physicians can screen for newly-admitted patients who could benefit from talking about their preferences and goals for end-of-life care. They can also monitor the progress and outcomes of these patients over time and adjust their treatment plans accordingly.
The researchers believe that this model can also help raise awareness and reduce stigma around death and dying among both patients and physicians. They hope that by sharing this information, they can help people make informed decisions about their health and quality of life.
However, there are also some ethical and social implications of using AI to predict death. For example, how would people feel if they knew they were going to die soon? Would they be scared or relieved? Would they try to prolong their lives or accept their fate? How would this affect their relationships with their loved ones?
Moreover, how would this affect the role and responsibility of physicians? Would they be able to provide adequate care for all patients regardless of their prognosis? Would they be able to respect the autonomy and dignity of each patient? Would they be able to cope with the emotional stress and trauma of losing some patients?
These are some of the questions that need to be addressed before AI can be widely used in healthcare settings. The researchers acknowledge that their model is not perfect and has some limitations. For example, it may not account for individual variations in health status, lifestyle factors, genetic mutations, environmental exposures, etc. It may also not capture all aspects of human life beyond physical health.
Therefore, they suggest that this model should be used as a tool rather than a substitute for human judgment and compassion. They also recommend that more research should be done to validate and improve this model in different populations and settings.
