Health AI now able to diagnose mental-health conditions better than psychiatrists

[Maciamo]

Here is another way artificial intelligence could soon revolutionise healthcare.

The Economist: AI offers an intriguing new way to diagnose mental-health conditions

Traditional methods of diagnosing mental-health conditions require patients to speak directly to a psychiatrist. Sensible in theory, such assessments can, in practice, take months to schedule and ultimately lead to subjective diagnoses.

That is why scientists are experimenting with ways to automate this process. Artificial-intelligence (AI) tools trained to listen to patients have proved capable of detecting a range of mental-health conditions, from anxiety to depression, with accuracy rates exceeding conventional diagnostic methods.

By analysing the acoustic properties of speech, these AI models can identify markers of depression or anxiety that a patient might not even be aware of, let alone able to articulate. Though individual features like pitch, tone and rhythm each play a role, the true power of these models lies in their ability to discern patterns imperceptible to a psychiatrist’s ears.

In summary:

AI tools are being developed to diagnose mental-health conditions by analyzing speech patterns, which can detect markers of depression or anxiety that patients may not be aware of.

These AI models analyze acoustic properties of speech, such as pitch, tone, and rhythm, and can discern patterns that are imperceptible to human ears.

Large language models (LLMs) have limitations in this field due to cultural nuances, language barriers, and different levels of fluency.

New methods under development focus on how words are spoken, not just the words themselves, such as an AI model from South-Central Minzu University in China that looks for subtle changes in a patient’s voice.

Another method from Sorbonne University in Paris analyzes sound waves recorded via a smartphone app to detect various mental-health conditions.

The potential applications of these technologies include easier patient assessment, cross-language functionality, and the ability to help triage and monitor patients.

 

[Hawk]

No doubt the technology of LLM and async transformers seems to be revolutionary, next step would probably be to make them computationally affordable which i think they want to achieve it with quantum computing then likely our civilization will enter some sort of next stage.

 

[mirimax]

The diagnosis of mental illnesses using artificial intelligence (AI) is still in its infancy, but can already deliver promising results - but as a supplement to human expertise rather than a replacement. AI can process large amounts of data and recognise patterns that help in diagnosis, for example by analysing speech patterns, behavioural data and even biometric data such as heart rate or sleep patterns.

It is not yet clear whether AI can make better diagnoses than an experienced psychiatrist. However, it can provide valuable support by making predictions and providing clues that psychiatrists can then analyse in more detail. However, interaction with the patient remains an important point: Empathy, understanding the context and building a trusting relationship are indispensable aspects of diagnosis and therapy that AI cannot currently provide.

 

[alonsodavies]

The diagnosis of mental illnesses using artificial intelligence (AI) is still in its infancy, but can already deliver promising results - but as a supplement to human expertise rather than a replacement. AI can process large amounts of data and recognise patterns that help in diagnosis, for example by analysing speech patterns, behavioural data and even biometric data such as heart rate or sleep patterns.

It is not yet clear whether AI can make better diagnoses than an experienced psychiatrist. However, it can provide valuable support by making predictions and providing clues that psychiatrists can then analyse in more detail. However, interaction with the patient remains an important point: Empathy, understanding the context and building a trusting relationship are indispensable aspects of diagnosis and therapy that AI cannot currently provide.
A misdiagnosis can cost lives. Implementation of AI will require many years of testing. Especially in psychiatry, where a human approach is important. AI cannot show empathy. It does not understand the context of the patient's life. Such systems should become as reliable as possible. But this will not happen soon. I am currently looking for research topics and thinking about the topic. I have been looking for healthcare research topics for college students for a very long time and I need it. You have given me a good idea. I will create a paper on the fact that people are not ready to trust a robot with their illnesses. Therefore, AI will be implemented in medicine last of all. Now it can only be an assistant for doctors.

It is still too early to talk about AI in the medical field. AI will be implemented there last of all because it is too risky.