Exosome SERS Signal Maps for Objective AI Mental Illness Diagnosis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mental illness diagnosis methods lack objective laboratory verification and struggle to distinguish between normal behavior and mental disorders, relying heavily on clinical symptoms without radiological or blood test validation.
Innovation Solution
A mental illness diagnosis system utilizing exosome Surface-Enhanced Raman Scattering (SERS) signals and artificial intelligence algorithms to classify and diagnose mental illnesses by learning from exosome SERS signal maps, distinguishing between normal and mental illness patients, and further classifying specific types of mental illnesses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If diagnosis is based on clinical symptoms and DSM criteria, then ease of operation is improved, but measurement precision deteriorates due to lack of laboratory verification
Solution Approach 1:
The patent replaces the manual clinical symptom assessment system with an automated AI-based diagnostic system that processes exosome SERS signal data. The AI algorithm analyzes molecular-level signals from exosomes to provide objective diagnosis, substituting the mechanical/subjective clinical evaluation process with an automated objective measurement system.
Solution Approach 2:
The patent introduces exosomes as an intermediary substance that carries biological information between cells. By detecting SERS signals from exosomes in body fluids, the system obtains objective molecular markers that mediate between the patient's condition and the diagnostic process, providing verified laboratory data without direct tissue biopsy.
2Measurement precision
If AI algorithm is trained using comprehensive exosome SERS signal maps, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the exosome SERS signal analysis into multiple functional components: signal acquisition unit, preprocessing unit, AI classification unit, and diagnosis unit. Each component handles specific tasks independently, making the complex AI-based system modular and manageable while maintaining high diagnostic precision through specialized processing at each stage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides objective diagnosis of mental illnesses with high accuracy, achieving sensitivity of 91.4% and specificity of 88.6%, enabling precise classification of mental disorders such as depression, bipolar disorder, schizophrenia, dementia, and delusional disorder.
Implementation Method 1
a signal acquisition unit configured to drop exosomes acquired from a measurement target person onto a chip including multiple dot arrays and acquire a signal map including multiple exosome SERS signals from the chip
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present disclosure relates to an artificial intelligence-based mental illness diagnosis system and method using exosome SERS signals. According to the present disclosure, a mental illness diagnosis system based on artificial intelligence using exosome SERS signals includes a first learning unit configured to cause a mental illness diagnosis algorithm to be learned to classify exosome SERS signals included in input signal maps into 0 and 1 by inputting a first signal map acquired by using exosomes acquired from a normal person and a second signal map acquired by using exosomes acquired from a mental illness patient to the mental illness diagnosis algorithm, a signal acquisition unit configured to drop exosomes acquired from a measurement target person onto a chip including multiple dot arrays and acquire a signal map including multiple exosome SERS signals from the chip, and a diagnosis unit configured to input the acquired signal map to the mental illness diagnosis algorithm for which learning is completed, acquire a signal value of 0 or 1 for each of the exosome SERS signals included in the signal map, and diagnose the measurement target person as the normal person or the mental illness patient by using an average of acquired signal values.