ReviewHealth data science2026
A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data.
Review in Health data science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Article
- Human intention recognition for trauma resuscitation: An interpretable deep learning approach for medical process data.Journal of biomedical informatics · 2025Article
- Individualized dynamic latent factor model for multi-resolutional data with application to mobile health.Biometrika · 2024Article
- Comparative Assessment of Multimodal Sensor Data Quality Collected Using Android and iOS Smartphones in Real-World Settings.Sensors (Basel, Switzerland) · 2024Article
- Automated hearing loss type classification based on pure tone audiometry data.Scientific reports · 2024Article
- Continuous patient state attention model for addressing irregularity in electronic health records.BMC medical informatics and decision making · 2024Article
- Deep imputation of missing values in time series health data: A review with benchmarking.Journal of biomedical informatics · 2023Review
- A self-supervised learning-based approach to clustering multivariate time-series data with missing values (SLAC-Time): An application to TBI phenotyping.Journal of biomedical informatics · 2023Article
- Deep multi-modal intermediate fusion of clinical record and time series data in mortality prediction.Frontiers in molecular biosciences · 2023Article
- Timing errors and temporal uncertainty in clinical databases-A narrative review.Frontiers in digital health · 2022Review
- Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters.Sensors (Basel, Switzerland) · 2021Article
- Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning.BMC medical informatics and decision making · 2021Article
- Predicting Risk of Mortality in Pediatric ICU Based on Ensemble Step-Wise Feature Selection.Health data science · 2021Article
- Addressing Noise and Skewness in Interpretable Health-Condition Assessment by Learning Model Confidence.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Identifiers
What OpenQuestion holds
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.