FOR PATIENTS
Your experience belongs in the picture.
DaiMIND Clinical is designed to help your clinician keep your priorities, strengths, everyday challenges, and changing circumstances in view.
Core intelligence. Purposeful applications.
DaiMIND organizes source information, preserves its meaning, and guides how AI interprets and expresses it. A shared foundation for clinical intelligence and interactive publications.
Source-linked
Purpose-led
Human-governed
A patient record and an authored publication need different kinds of interpretation. Both need information that retains its source, context, uncertainty, and the human decisions that govern its use.
DaiMIND brings those information-handling principles together. Its clinical and publication modules add the methods, vocabulary, and boundaries appropriate to their work. Prepared material can support an output directly; explicit modeling is used where the application calls for it.
DAIMIND CLINICAL
Clinical information becomes an individualized account of difficulties, strengths, goals, and context. Different people need different views of that understanding.
FOR PATIENTS
DaiMIND Clinical is designed to help your clinician keep your priorities, strengths, everyday challenges, and changing circumstances in view.
FOR PROVIDERS
Connect the record to a patient-specific formulation and useful clinical outputs. Retain authority over interpretation, priorities, and revision.
FOR SYSTEMS
Support continuity, handoffs, and longitudinal review while keeping the clinical understanding distinct from each service’s documentation requirements.
FOR REVIEWERS
Examine supporting information, uncertainty, and gaps when considering a determination. Administrative criteria guide the review task; they do not define the person’s clinical formulation.
In development and validation. Patient-facing use is intended to remain under clinician direction; this site introduces the work.
THE CLINICAL METHOD
From source information to individualized understanding, useful outputs, and deliberate revision. Select a stage to see its role.
01 / DATA
Clinical records, patient reports, collateral information, observations, and measures enter with their source and status intact.
02 / DECOMPOSITION & CLARIFICATION
Identify clinically useful variables, preserve uncertainty, and ask questions that could change the understanding of this person.
03 / PATIENT MODEL
Bring together the interacting functions and circumstances that help explain difficulties, ordinary functioning, and thriving.
04 / PROJECTION
Use the authorized clinical understanding to support a formulation, handoff, patient explanation, or other requested output.
05 / UPDATE
New observations and intervention experiences can prompt a review of the working formulation. Changes in interpretation remain clinician-led.
DESIGN PRINCIPLES
Each application defines what information may be used and how it may be transformed.
Important conclusions retain a path back to their sources, assumptions, conflicts, and revisions.
Source changes and human decisions can be carried forward without erasing the basis of earlier outputs.
Clinicians, authors, and editors retain the authority appropriate to their work. AI-generated content does not approve itself.
DAIMIND PUBLICATION
Prepared source material can support questions, explanations, learning materials, and other permitted transformations. Each publication keeps its own editorial direction and boundaries.
Help readers explore an authored body of work while keeping meaning and source context recoverable.
An author-led service for developing interactive editions. Private pilot; access may be required.
The goal is not to make AI sound more clinical. It is to make clinical reasoning more explicit, testable, and useful.
RESEARCH & DEVELOPMENT
DaiMIND is being developed by Gerrit van Schalkwyk, MD, a psychiatrist, clinical neuroscience educator, and physician working across care delivery and utilization management.
The research program examines source fidelity, useful clinical understanding, and the effect of explicit governance on AI outputs. Evidence for each application will be evaluated separately.
Currently in development and validation.
DAIMIND