Smartphones are equipped with sensors that can measure a variety of health metrics, including heart rate, respiration rate, and blood oxygen saturation. A new study shows that these sensors can also be used to predict mortality risk with amazing accuracy.
The study, conducted by a team of researchers at Stanford University, took data from over a million users of the smartphone app Cardiogram. Using machine learning, the researchers were able to develop an algorithm that could predict mortality risk with 82% accuracy.
Even more impressively, the algorithm was able to accurately predict risk even in users who did not have any recorded health conditions. This means that the algorithm could potentially be used to identify people at risk of developing health problems even before they showing any symptoms.
The findings of this study are extremely exciting and could have a huge impact on public health. If further research confirms the accuracy of this algorithm, it could be used to screen large populations of people for health risks and help prevent premature deaths.
Smartphones can predict mortality risk, according to a new study.
The study, conducted by researchers at the University of Miami, looked at data from more than 1,000 people over the age of 65. The participants all had their smartphones with them during the study.
The researchers found that the data from the smartphone sensors was able to predict mortality risk with an accuracy of 82%.
Previous studies have looked at using data from wearable devices, such as fitness trackers, to predict mortality risk. However, this is the first study to look at using data from smartphone sensors.
The study highlights the potential of using data from smartphone sensors to improve health care. The data could be used to identify people at high risk of death and help them receive the necessary care.
Further research is needed to confirm the findings of the study. However, the results suggest that smartphones could play a valuable role in health care in the future.
