The healthcare industry is undergoing a momentous change in the way it approaches diagnosis and treatment of diseases with the advent of Artificial Intelligence (AI).
One area where its potential impact is particularly significant is in the realm of depression, which affects 300 million people worldwide and accounts for a significant portion of global ill health.
Depression Detection Difficulties
For clinicians, diagnosing depression is not easy. There isn’t any one test that can be done hence doctors use self-reported symptoms, questionnaires and observations ultimately resulting in less than 50% pick-up rates by general practitioners.
Depression presents differently from individual to individual hence making it difficult to accurately diagnose.
The Role of AI in Diagnosis Revolution
Enthusiasm is growing about how artificial intelligence through learning, reasoning and self-correction could transform how depression is diagnosed and treated.
Through artificial intelligence, machine learning uses data analysis to detect patterns without human intervention.
AI studies in recent times have produced interesting results when it comes to diagnosing depression.
In simulated cases with different levels of depression severity, gender and social class, AI models predominantly recommended talk therapy as the first line intervention, consistent with guidelines from the US, UK, and Australia.
On the other hand, human doctors generally prescribed antidepressants implying that AI follows clinical recommendations much more closely.
Furthermore, AI has been shown as having lower biases towards gender or socio-economic status unlike human doctors who statistically tend to over-prescribe antidepressants to men especially those employed in blue-collar jobs.
Brain Implications on Depression Unveiled
Scientists have also found that depression affects specific brain regions in a similar manner across individuals.
It has been possible to predict depression by examining these brain structures using MRI scans with an accuracy rate above 80%.
Using both structural and functional MRI data increases prediction accuracy above 93%, indicating the possibility of incorporating multiple imaging methods for better AI based diagnosis processes.
Although MRI-based AI tools are restricted to research at the moment, developments in the accessibility and portability of MRI technology suggest that it could become part of routine medical practice in future.
The Rise of Wearable Gadgets
Smartwatches and other wearable devices are becoming popular as tools for detecting and predicting depression.
Such gadgets collect diverse information like heart rate, sleep patterns and activity levels, which enables depression predictions with accuracy rates between 70% – 89%.
However, issues such as cost, potential bias in data collection across demographic groups and limited representation in terms of study population size must be resolved.
Mining Social Media Data
AI-powered analyses of language used in social media posts have shown promising results in predicting depression, achieving success rates of up to 90% in English and Arabic.
Even the use of emojis has been found to indicate depression hence early detection possibilities.
Predicting Treatment Outcomes
Artificial intelligence is not only helping with diagnosing cases but also predicting how patients will respond to treatment.
On top of that, it has been proven that electronic health records can predict antidepressant responses with more than 70% accuracy.
This ability could be crucial when it comes to prescribing medication-based treatments by giving physicians concrete evidence thus improving their outcomes.
Future Outlooks: Validation
Although AI has a promising potential for diagnosing and managing depression, there is a need to validate the recent findings before widely relying on these tools in clinical practice.
In the meantime, MRI scans, wearables and social media analyses may be useful complements to doctors’ diagnosis and treatment of depression.
In conclusion, the growing developments in artificial intelligence give hope for redefining the field of diagnosis and treatment for depression by providing medical practitioners with more accurate diagnostic tools as well as personalized treatment options.