Artificial Intelligence (AI) has invaded the healthcare sector long back. It is making accountable impacts on treatment and overviewing of patients. However, psychiatry department stands out when it comes to utilising AI applications. It has taken a long way before reaching the current initial stage where AI is being used for analyzing patients but only by a handful of psychiatrists.

Medicine is already reaping a fruitful benefit from artificial intelligence and big data. It has shown promising results in diagnosing disease, interpreting images and concentrating on treatment plans. Though psychiatry is in many ways a uniquely human field, requiring emotional intelligence and perception that computers can’t stimulate, experts say that AI could have an impact. The field could profit from artificial intelligence’s ability to analyze data and pick up on patterns and warning signs so subtle humans might never notice them.

However, connecting psychiatry with artificial intelligence and big data is not an easy job. Psychiatrists and behavioral health researchers found it difficult to make the connection on how to implement artificial intelligence into actual psychiatry use cases. Today, both medicine and technology are breaking their barriers to make a change.

Use cases of AI and its Applications in Psychiatry

####### Predictive modeling

Predictive modeling is generally building machine learning algorithms that are used to predict future events by utilizing historical data. Predictive modeling in psychiatry is aiding doctors to predict which treatment is likely to work for patients with issues like anxiety and depression. Generally, doctors segment patients on three rows according to their response to the treatment.

• Early responders, Patients who responded in the first two years of treatment
• Late responders, Patients who responded between two and five years of treatment
• Non-responders, Patients who continued to suffer even after five years of treatment

Before the invasion of artificial intelligence, doctors used to manually segment the patients according to clinical intuition, presentation and history to predict which group the patient belonged to. However, most of the human analysis was mere guesses rather than accurate answers. This swayed the treatment from being exact to somewhere close it. Henceforth, utilizing artificial intelligence with predictive modeling would help improve the matching of the patients to the right group, so the right treatment can be started quickly.

Classifying and concentrating on non-responders is a critical task. They are patients who need immediate attention. Artificial intelligence segregates them and indicates it to the psychiatrist who can show special care for the needy.

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