ReviewBuilding and environment2026
Data-driven estimation of core body temperature during physical activity under heat exposure: A systematic review and standardized evaluation.
Review in Building and environment, 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate, real-time estimation of core body temperature (CBT) during physical activity is essential for monitoring heat strain and mitigating the risk of heat-related illness under hot environmental conditions. Although numerous data-driven algorithms using wearable sensors have been proposed, their practical reliability remains unclear due to substantial methodological heterogeneity and the absence of standardized evaluation. This study combined a systematic review with a standardized quantitative benchmark. A total of 38 studies employing non-invasive inputs for CBT estimation were identified. Of these, 14 eligible models, including Kalman filter-based methods, statistical models, and machine-learning approaches, were re-implemented and evaluated under identical preprocessing and evaluation settings using two independent datasets: Dataset 1 (treadmill walking,
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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.