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Clinical researchers, computational psychiatry groups, healthcare AI builders, and Institute fellows.

Active Inference and Healthcare

A research scaffold for clinical, computational psychiatry, and health-system applications.

Mejores acciones siguientes

Active Inference and Healthcare pathway

Comience con los enlaces públicos de mayor señal para esta página, luego continúe a través de las vistas de recursos y directorios relacionados.

Healthcare applications of Active Inference treat symptoms, clinical decisions, monitoring, and adaptive support as problems of perception, action, uncertainty, and model updating.

Why the domain fits

Clinical care involves latent-state inference, uncertain observations, action under risk, and changing preferences over health outcomes. Active Inference gives researchers a shared language for modeling those loops without reducing care to a single prediction task.

Application pattern

A domain report should separate three layers: formal models of symptoms or physiology, decision-support systems that choose information-gathering or intervention policies, and institutional workflows for accountable clinical use.

Evidence to collect next

The next pass should identify reviewed computational psychiatry papers, clinical waveform or monitoring work, active sensing use cases, and implementation repositories. Each claim should land in the citation registry before it appears on the public page.

Reference Backbone

Karl J. Friston (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience. DOI: 10.1038/nrn2787. Christopher L. Buckley, Chang Sub Kim, Simon McGregor, Anil K. Seth (2017). The free energy principle for action and perception: A mathematical review. Journal of Mathematical Psychology. DOI: 10.1016/j.jmp.2017.09.004. Thomas Parr, Giovanni Pezzulo, Karl J. Friston (2022). Active Inference: The Free Energy Principle in Mind, Brain, and Behavior. MIT Press. Giovanni Pezzulo, Francesco Rigoli, Karl J. Friston (2017). Active Inference, homeostatic regulation and adaptive behavioural control. Progress in Neurobiology. DOI: 10.1016/j.pneurobio.2017.08.001.

Superficies clave

Active Inference and Healthcare at a glance

Clinical modeling

Represent symptoms, beliefs, uncertainty, and regulation as coupled inference and action processes.

Decision support

Frame monitoring and intervention as policy selection under uncertainty, with explicit confidence and review boundaries.

Publication boundary

Public pages should distinguish reviewed literature, Institute projects, and speculative research leads.

Recursos relacionados

Enlaces públicos para esta página

Los enlaces externos se resuelven desde el registro compartido, por lo que los destinos orientados al visitante permanecen centralizados y verificables.

Repository / Projects

GitHub organization

Audience: Developer

Public GitHub organization for Institute repositories and open-source work.

projectsgithub-org
Repository / Projects

GEO-INFER repository

Audience: Developer

Geospatial modeling repository connected to ecological and bioregional applications.

projectsgeo-infer

Páginas oficiales

Superficies institucionales oficiales

Repositorios

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Repository / Research

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Audience: Researcher

Computational meta-analysis of Active Inference literature with nanopublication and knowledge-graph outputs.

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Repository / Research

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Ontology-oriented repository for shared Active Inference concepts and decentralized science knowledge infrastructure.

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Notebook-based applied Active Inference work connected to blockchain-adjacent and generative modeling examples.

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Audience: Developer

Python models and materials for ant-inspired multiagent Active Inference.

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Active Entity Ontology for Science

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Repository / Projects

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Audience: Developer

Public ants repository in the ActiveInferenceInstitute GitHub namespace.

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