Observational studyMedicine2020
Health outcome prediction using multiple perturbations.
Observational study in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Technology-free predictors of preterm birth in singleton women with threatened preterm labor: a prospective cohort study.BMC pregnancy and childbirth · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Public health workers and medical practitioners are frequently required to make predictions regarding various health outcomes. However, a prediction with nearly 100% certainty is seldom possible.If a person has a health outcome of concern or is in the process of developing the outcome, many attributes of that person may undergo subtle changes-the perturbations. We propose a method, namely "prediction using multiple perturbations" and investigate its asymptotic properties when the number of attributes tends to infinity. This is a proof-of-concept study.The proposed method can predict the health outcome of a person to near certainty if personal data with billions or trillions of attributes can be collected and 4 conditions (described subsequently in this paper) are met.Collecting personal data with billions or trillions of attributes may someday become possible in the current era of big data. If such information can be obtained, theoretically we can predict the health outcome of a person to near certainty.
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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.