ArticleChronic stress (Thousand Oaks, Calif.)
Data Science in the Research Domain Criteria Era: Relevance of Machine Learning to the Study of Stress Pathology, Recovery, and Resilience.
Article in Chronic stress (Thousand Oaks, Calif.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Predicting psychological resilience in older adults during the COVID-19 pandemic: a machine learning approach.The Gerontologist · 2025Article
- Applications of artificial intelligence-machine learning for detection of stress: a critical overview.Molecular psychiatry · 2024Review
- A machine-learning approach to investigating the complexity of theory of mind in individuals with schizophrenia.Heliyon · 2024Article
- Machine Learning Approaches to Understand Cognitive Phenotypes in People With HIV.The Journal of infectious diseases · 2023Article
- Predicting benzodiazepine prescriptions: A proof-of-concept machine learning approach.Frontiers in psychiatry · 2023Article
- Modern views of machine learning for precision psychiatry.Patterns (New York, N.Y.) · 2022Review
- Pre-trauma predictors of severe psychiatric comorbidity 5 years following traumatic experiences.International journal of epidemiology · 2022Article
- Predicting Posttraumatic Stress Disorder Among Survivors of Recent Interpersonal Violence.Journal of interpersonal violence · 2022Article
- Psychiatric Neural Networks and Precision Therapeutics by Machine Learning.Biomedicines · 2021Review
- Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.PloS one · 2021Article
- The resilience paradox.European journal of psychotraumatology · 2021Article
- Supervised Machine Learning: A Brief Primer.Behavior therapy · 2020Review
- Ontological representation-oriented term normalization and standardization of the Research Domain Criteria.Health informatics journal · 2020Article
- The role of RDoC in future classification of mental disorders .Dialogues in clinical neuroscience · 2020Review
- A Unique Brain Connectome Fingerprint Predates and Predicts Response to Antidepressants.iScience · 2020Article
- Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2019Article
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
Abstract
Diverse environmental and biological systems interact to influence individual differences in response to environmental stress. Understanding the nature of these complex relationships can enhance the development of methods to: (1) identify risk, (2) classify individuals as healthy or ill, (3) understand mechanisms of change, and (4) develop effective treatments. The Research Domain Criteria (RDoC) initiative provides a theoretical framework to understand health and illness as the product of multiple inter-related systems but does not provide a framework to characterize or statistically evaluate such complex relationships. Characterizing and statistically evaluating models that integrate multiple levels (e.g. synapses, genes, environmental factors) as they relate to outcomes that a free from prior diagnostic benchmarks represents a challenge requiring new computational tools that are capable to capture complex relationships and identify clinically relevant populations. In the current review, we will summarize machine learning methods that can achieve these goals.
Indexed as
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.