Thomas McGinn, chairman of medicine at a major New York hospital system, is betting he can predict if a patient has strep, pneumonia or other ailments not by ordering traditional lab tests or imaging scans, but by calculating probabilities with a software program. Dr. McGinn believes using technology to help diagnose and treat patients can reduce the large number of unnecessary tests doctors order and antibiotics they prescribe by ruling out certain diseases. It also could expedite the appropriate care for patients by giving doctors grounds to treat them before lab tests can confirm a diagnosis. The predictive tool, which pops up on the screen of electronic medical records, prompts the doctor to answer a short series of questions about the patient's condition. Based on that information, a calculator predicts the probability that the person has the suspected ailment.
Engineers and physicians at Ohio State University have teamed up to give doctors the ability to see how a patient's heart is likely to react to surgery, before the surgery even begins. Experts at Ohio State's Wexner Medical Center use CT scans to map out a patient's heart for the model. Using 3-D printing, the team creates a model of a patient's heart. This allows doctors to study a model that exactly matches the patient's heart, including any defects. These models are then placed in machines that can simulate the effects of the stress of an actual working heart.
Big data has made an incredible advancement in technology over the past couple of years. It has been proven to be effective with it's ability to find and collect different types of data. Big data has not only helped to pilot the technology behind artificial traffic lights but has specifically shown an improvement in the medical world. Big data has been able to equip doctors with enough data about their patient's medical history to provide improved beneficial care. Today we see big data playing a part in biomedical research.
Google is universally well known as a search and advertising company. Now Google is tapping into the $3.5 trillion health care market. To compete with the Apple Watch, Google acquired Fitbit, the wearable exercise, heart rate and sleep tracking device. Voluntarily worn fitness tracking devices are one thing, but Google has entered the realm of the brave new world. A government inquiry has brought to light Google's "Nightingale Project" that collected private medical data from Ascension Health's 2,600 sites of care across 20 states and D.C., unbeknownst to the patients.
A new artificial intelligence system developed by researchers at the University of Washington uses patient data to predict whether patients are at risk of abnormally low blood oxygen (hypoxia) during surgery. University of Washington (UW) researchers have developed an artificial intelligence (AI) system that uses patient data to predict whether patients are at risk of abnormally low blood oxygen (hypoxia) during surgery. The Prescience system also provides users with real-world explanations to support and explain its predictions. In collaboration with physicians, UW's Su-In Lee and colleagues trained Prescience on about 50,000 patient files, so the program could analyze data such as patient age and weight to calculate the likelihood of hypoxemia prior to surgery. The system also uses real-time data during surgery to predict when patients are in danger of hypoxemia, and a new AI model helps Prescience provide doctors a concise description of the prediction's underlying factors.