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Natural, Traditional & Alternative Medicine
2021-06-07 - 2021-06-08    
All Day
Natural, Traditional and Alternative Medicine mainly focuses on the latest and exciting innovations in every area of Natural Medicine & Natural Products, Complementary and Alternative [...]
Advances In Natural Medicines, Nutraceuticals & Neurocognition
2021-06-11 - 2021-06-12    
All Day
The two-days meeting goes to be an occurrence to appear forward to for its enlightening symposiums & workshops from established consultants of the sphere, exceptional [...]
Automation and Artificial Intelligence
2021-06-15 - 2021-06-16    
All Day
Conference Series invites all the experts and researchers from the Automation and Artificial Intelligence sector all over the world to attend “2nd International Conference on [...]
Green Chemistry and Technology 2021
2021-06-23 - 2021-06-24    
All Day
Green Chemistry and Technology is a global overview with the Theme:: “Sustainable Chemistry and its key role in waste management and essential public service to [...]
Food Science & Nutrition
2021-06-25 - 2021-06-26    
All Day
Food Science is a multi-disciplinary field involving chemistry, biochemistry, nutrition, microbiology, and engineering to give one the scientific knowledge to solve real problems associated with [...]
Food Safety and Health
2021-06-28 - 2021-06-29    
All Day
The main objective is to bring all the leading academic scientists, researchers and research scholars together to exchange and share their experiences and research results [...]
Food Microbiology
2021-06-28 - 2021-06-29    
All Day
This conference provide a platform to share the new ideas and advancing technologies in the field of Food Microbiology and Food Technology. The objective of [...]
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Articles News

A study shows that AI can detect suicide risk early.

EMR Industry

As artificial intelligence helps doctors discover diseases like cancer at an early stage, it is also demonstrating its potential in tackling mental health crises. According to one study, artificial intelligence can detect patients who are at danger of suicide, providing a tool for prevention in everyday medical settings.

The study, published in the JAMA Network Open Journal, examined two approaches of notifying doctors about suicide risk: an active “pop-up” alarm demanding immediate attention and a passive system (less urgent) that displays risk information in a patient’s electronic chart.

The study discovered that active warnings beat the passive strategy, encouraging doctors to assess suicide risk in 42% of cases, against only 4% with the passive system. Furthermore, it emphasized the importance of using certain techniques to initiate a discourse about suicide risks.

This breakthrough, which combines automated risk identification with deliberately tailored alarms, provides hope for identifying and supporting more people in need of suicide prevention services.

Colin Walsh, an Associate Professor of Biomedical Informatics, Medicine, and Psychiatry at Vanderbilt University Medical Center, emphasized the importance of this breakthrough. “Most people who die by suicide have seen a healthcare provider in the year before their death, often for reasons unrelated to mental health,” according to Walsh.

Previous research indicates that 77% of people who commit suicide had contact with primary care doctors in the year before their death. These findings highlight the essential role AI can play in bridging the gap between conventional medical treatment and mental health interventions.

The Suicide Attempt and Ideation Likelihood model (VSAIL), an AI-driven system developed at Vanderbilt, was tested in three neurology clinics. The method uses normal data from electronic health records to calculate a patient’s 30-day probability of attempting suicide. When high-risk patients were identified, practitioners were encouraged to start focused conversations about mental health.

Walsh clarified: “Universal screening isn’t practical everywhere, but VSAIL helps us focus on high-risk patients and spark meaningful screening conversations.”

While the findings were promising, the researchers emphasized the importance of striking a balance between the benefits of active alerts and their possible drawbacks, such as workflow disruption. The authors proposed that comparable methods may be implemented for other medical specialties in order to broaden their reach and impact.

Cambridge University published a research earlier in 2022 that used PRISMA criteria to assess individuals who were at risk of attempting suicide.