Helping patients following a stroke: In emergency rooms, when patients come in with a stroke called an intracerebral hemorrhage, they undergo a CT scan. That scan is examined by a computer trained to analyze CT data, cutting the time to diagnosis and limiting brain damage. Preventing heart problems: Applying AI to ECGs has resulted in a low-cost test that can be widely used to detect the presence of a weak heart pump, which can lead to heart failure if left untreated. Mayo Clinic is well situated to advance this use of AI because it has a database of more than 7 million ECGs. First, all identifying patient information is removed to protect privacy.

In healthcare, the highest risk individuals for morbidity and mortality are rarely those with the greatest modifiable risk. By contrast, many machine learning formulations implicitly attend to the highest risk individuals. We focus on this problem in point processes, a popular modeling technique for the analysis of the temporal event sequences in electronic health records (EHR) data with applications in risk stratification and risk score systems. We show that optimization of the log-likelihood function also gives disproportionate attention to high risk individuals and leads to poor prediction results for low risk individuals compared to ones at high risk. We characterize the problem and propose an adjusted log-likelihood formulation as a new objective for point processes. We demonstrate the benefits of our method in simulations and in EHR data of patients admitted to the critical care unit for intracerebral hemorrhage.

The number of CT scans hospitals perform is on the rise, but professionals who actually read these scans can't seem to keep up with increasing demand -- often just looking at images as they come in. But artificial intelligence may be able to help. Chicago startup Realize.ai is launching a pilot study of its AI that identifies certain problems often spotted on CT scans this fall at Northwestern University Medical Center. Many times, these scans can reveal deadly conditions that need immediate attention, which means reading scans efficiently can be a life-or-death situation. "Getting to a scan too late or misreading a scan can cause serious clinical problems and we are trying to alleviate that," said co-founder Alex Risman.