ArticleDelaware journal of public health2026
Human-AI Cooperation in Healthcare and Rehabilitation.
Article in Delaware journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rehabilitation after injury or to manage chronic health conditions requires continuous reassessment and intervention across time scales ranging from seconds to months. Advances in sensors and data collection, coupled with new technology to administer interventions, create numerous possibilities-including at-home care. The increased capabilities enable automated analysis and control using artificial intelligence (AI). In this essay, we analyze the need, the potential and the requirements for an intense and enduring physical human-AI cooperation framework, i.e., a symbiosis, where both AI and humans contribute to realize improved solutions. The focus is the development of knowledge and expertise to realize a new generation of AI-enabled therapy for the next decades. With an aging population, prevalence of stroke and chronic diseases, there is a demand for more efficient and effective rehabilitation powered by human-AI cooperation, especially in cases that enable remote participation in areas with limited access. This essay analyzes how the potential for advances in human-AI cooperation can impact rehabilitation in Delaware.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.