The widespread implementation of electronic health records (EHRs) has proved to be a bumpy ride for many. But the sheer amount of data available in digital form carries with it plenty of potential. Recent work by scientists from IBM and Sutter Health developed artificial intelligence that can uncover pre-diagnostic heart failure through EHRs. A study, published in Circulation: Cardiovascular Quality and Outcomes, included a model that used 1,684 heart failure cases along with 13,525 sex, age-category and clinic matched controls for modeling purposes. "Model performance was most strongly influenced by the diversity of data, basic feature construction and the length of the observation window," wrote Kenny Ng, research staff member in the Center for Computational Health and first author of the study. "In raw form, EHR data are highly diverse, represented by thousands of variants for disease coding, medication orders, laboratory measures, and other data types.

In this week's Abundance Insider: Self-organizing drone swarms, synthetic stem cells, and an AI that can detect heart failure better than human doctors. I'm launching an online course with SUCCESS Magazine called Xponential Advantage. It's aimed to inspire, educate and guide a new breed of "Exponential Entrepreneurs," and is an expansion of my core content from Abundance and BOLD, the keynotes I give to Fortune 500 executive teams, and some of the material I teach executives who attend Singularity University. These are the areas I truly believe an exponential entrepreneur can leverage to have a billion-person impact. What it is: Scientists at the London Institute of Medical Services have created an AI capable of predicting with 80% accuracy which patients would die of pulmonary hypertension within a year, beating the average doctor's prediction accuracy by about 20%.

An artificial intelligence system has accurately predicted when patients with heart conditions will die, according to new results published in the journal Radiology. The study was conducted by a team of scientists at the London Institute of Medical Services, who trained the software to analyze blood tests and intricate 3D models of beating hearts in order to detect signs of failure. The AI was assigned 256 patients diagnosed with pulmonary hypertension, a type of high blood pressure which impacts the lungs and can cause dizziness, fainting, and shortness of breath. By tracking the movement of 30,000 different points on a patient's heart, it was able to construct an intricate 3D scan of the organ. Combining these models with patient health records going back eight years, the system could learn which abnormalities signaled a patient's approaching death, making predictions about five years into the future.

The last place you want to learn you have heart failure is where it often winds up being diagnosed: in the emergency room. Researchers analyzing electronic health records are using artificial intelligence and GPUs to get ahead of this curve. They've shown they can predict heart failure as much as nine months before doctors can now deliver the diagnosis. A research team from Sutter Health, a Northern California not-for-profit health system, and the Georgia Institute of Technology, believe their method has the potential to reduce heart failure rates and possibly save lives. "The earlier we can detect the disease, the more likely we can change health outcomes for people and improve their quality of life," said Andy Schuetz, a senior data scientist at Sutter Health and an author of a paper describing one aspect of the research.

The last place you want to learn you have heart failure is where it often winds up being diagnosed: in the emergency room. Researchers analyzing electronic health records are using artificial intelligence and GPUs to get ahead of this curve. They've shown they can predict heart failure as much as nine months before doctors can now deliver the diagnosis. A research team from Sutter Health, a Northern California not-for-profit health system, and the Georgia Institute of Technology, believe their method has the potential to reduce heart failure rates and possibly save lives. "The earlier we can detect the disease, the more likely we can change health outcomes for people and improve their quality of life," said Andy Schuetz, a senior data scientist at Sutter Health and an author of a paper on the research.