pomodoren / comorbid-graphs

Side by side comparison of disorders based on comorbidity factors for clinical psychology.
MIT License
0 stars 0 forks source link
graph neuropsychology psychology

Comorbid-Graphs

Side by side comparison of disorders based on comorbidity factors for clinical psychology.

  1. create hierarchies of sources of information
  2. extract valuable elements from text
  3. visualize dependencies

Simple Example

Create from sample file:

from comorbid_graphs import ComorbidGraph
my_graph = ComorbidGraph.from_yaml('big_picture.yaml')

print(my_graph.explore(maxlevel=4))

Results:

Diagnosing Mental Health Issues
├── Frameworks
│   ├── DSM-V
│   │   ├── what
│   │   ├── where
│   │   │   ├── wikipedia
│   │   │   ├── website
│   │   │   └── manual
│   │   ├── who
│   │   │   └── APA
│   │   ├── elements
│   │   │   ├── disorder
│   │   │   ├── symptom
│   │   │   └── diagnostic guideline
│   │   └── mini versions
│   │       ├── Chinese Classification of Mental Disorders
│   │       │   └── wikipedia
│   │       └── Psychodynamic Diagnostic Manual
│   │           └── wikipedia
│   ├── ICD-10
│   │   ├── what
│   │   ├── where
│   │   │   ├── website
│   │   │   ├── manual
│   │   │   └── wikipedia
│   │   ├── who
│   │   │   └── WHO
│   │   └── elements
│   │       └── disorder
│   ├── HiTOP
│   │   ├── what
│   │   ├── where
│   │   │   ├── website
│   │   │   └── manual
│   │   └── elements
│   │       ├── spectra
│   │       ├── subfactor
│   │       ├── syndrome
│   │       ├── maladaptive trait
│   │       ├── symptoms
│   │       └── disorder
│   └── RDoC
│       ├── what
│       ├── where
│       │   ├── website
│       │   └── wikipedia
│       ├── who
│       │   └── nimh
│       └── elements
│           ├── genes
│           ├── molecules
│           ├── cells
│           ├── circuits
│           ├── physiology
│           ├── behaviors
│           ├── self-reports
│           └── paradigms
└── approaches
    ├── authoritative
    ├── psychodynamic
    ├── empirical
    └── network

Additional Resources

References

This package can be thought as a thin wrapper to Anytree, with some useful functionalities for use-case of ontologies and text-processing.