This task is especially challenging when dealing with observational data, as using such data runs the risk of hidden confounders whose existence can lead to biased and harmful policies.

Check out all the on-demand sessions from the Intelligent Security Summit here. How does a medical professional stay aware of the right procedures and treatments for patient ailments in the modern world? While many often rely on experience, there is another way that could have life-saving consequences. The trick is, it relies heavily on the power of artificial intelligence (AI). New York-based medical startup H1 released a new update to its HCP Universe platform today to inject a dose of healthcare AI into medical intelligence.

When you picture a hospital radiologist, you might think of a specialist who sits in a dark room and spends hours poring over X-rays to make diagnoses. Contrast that with your dentist, who in addition to interpreting X-rays must also perform surgery, manage staff, communicate with patients, and run their business. When dentists analyze X-rays, they do so in bright rooms and on computers that aren't specialized for radiology, often with the patient sitting right next to them. Is it any wonder, then, that dentists given the same X-ray might propose different treatments? "Dentists are doing a great job given all the things they have to deal with," says Wardah Inam SM '13, PhD '16.

When you picture a hospital radiologist, you might think of a specialist who sits in a dark room and spends hours poring over X-rays to make diagnoses. Contrast that with your dentist, who in addition to interpreting X-rays must also perform surgery, manage staff, communicate with patients, and run their business. When dentists analyze X-rays, they do so in bright rooms and on computers that aren't specialized for radiology, often with the patient sitting right next to them. Is it any wonder, then, that dentists given the same X-ray might propose different treatments? "Dentists are doing a great job given all the things they have to deal with," says Wardah Inam SM '13, Ph.D. '16.

When you picture a hospital radiologist, you might think of a specialist who sits in a dark room and spends hours poring over X-rays to make diagnoses. Contrast that with your dentist, who in addition to interpreting X-rays must also perform surgery, manage staff, communicate with patients, and run their business. When dentists analyze X-rays, they do so in bright rooms and on computers that aren't specialized for radiology, often with the patient sitting right next to them. Is it any wonder, then, that dentists given the same X-ray might propose different treatments? "Dentists are doing a great job given all the things they have to deal with," says Wardah Inam SM '13, PhD '16.

An international team of scientists, including a Western University researcher, have developed an artificial intelligence (AI) tool that facilitates more personalized treatments for depression and improves patient outcomes. "Our clinical trial shows that this new method of treatment selection improves the effectiveness of currently available treatments, with a small and affordable increase in overall treatment costs, since it fast-tracks more patients to intensive treatments when they need them," said Shehzad Ali, professor of public health economics at the Schulich School of Medicine & Dentistry. Ali, a Canada Research Chair in Public Health Economics, was the lead health economist and statistician on the study, which was led by the University of Sheffield in the U.K. Current practice for treating depression often involves a stepped care approach. Patients are first offered a low-intensity treatment, such as group therapy, with those who remain unwell later being moved to more intensive, lengthy treatment. The researchers behind the new tool have shown that implementing AI helps patients receive more tailored care to treat their depression much quicker.

Scientists at UCL have used artificial intelligence (AI) to identify three new multiple sclerosis (MS) subtypes. Researchers say the groundbreaking findings will help identify those people more likely to have disease progression and help target treatments more effectively. MS affects over 2.8 million people globally and 130,000 in the UK, and is classified into four* 'courses' (groups), which are defined as either relapsing or progressive. Patients are categorised by a mixture of clinical observations, assisted by MRI brain images, and patients' symptoms. For this study, published in Nature Communications, researchers wanted to find out if there were any - as yet unidentified - patterns in brain images, which would better guide treatment choice and identify patients who would best respond to a particular therapy.

The psychiatry field has long sought answers to explain why antidepressants help only some people. Is a patient's recovery due merely to a placebo effect – the self-fulfilling belief that a treatment will work – or can the biology of the person influence the outcome? Two studies led by UT Southwestern provide evidence for the impact of biology by using artificial intelligence to identify patterns of brain activity that make people less responsive to certain antidepressants. Put simply, scientists showed they can use imaging of a patient's brain to decide whether a medication is likely to be effective. The studies include the latest findings from a large national trial (EMBARC) intended to establish biology-based, objective strategies to remedy mood disorders and minimize the trial and error of prescribing treatments.

Harnessing cutting-edge technologies could bring new hope for people with heart and circulatory disease. In the first of a new series, Sarah Brealey learns how artificial intelligence could help treat heart failure. If you're diagnosed with a disease, you probably want to know what the future holds. But with some conditions, it's hard for your doctor to be certain. Pulmonary hypertension is a rare condition that damages the right side of the heart.