ArticleFrontiers in psychology2019
Malingering Detection of Cognitive Impairment With the b Test Is Boosted Using Machine Learning.
Article in Frontiers in psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Diagnosis of Pain Deception Using Minnesota Multiphasic Personality Inventory-2 Based on XGBoost Machine Learning Algorithm: A Single-Blinded Randomized Controlled Trial.Medicina (Kaunas, Lithuania) · 2024Trial
- Performance validity testing: the need for digital technology and where to go from here.Frontiers in psychology · 2024Article
- Reconstructing individual responses to direct questions: a new method for reconstructing malingered responses.Frontiers in psychology · 2023Article
- Human-like problem-solving abilities in large language models using ChatGPT.Frontiers in artificial intelligence · 2023Article
- Symptom and Performance Validity Assessment in European Countries: an Update.Psychological injury and law · 2022Review
- Article
- Translational Application of a Neuro-Scientific Multi-Modal Approach Into Forensic Psychiatric Evaluation: Why and How?Frontiers in psychiatry · 2021Article
- Detecting Cognitive Impairment Status Using Keystroke Patterns and Physical Activity Data among the Older Adults: A Machine Learning Approach.Journal of healthcare engineering · 2021Article
- Facial Emotion Recognition Predicts Alexithymia Using Machine Learning.Computational intelligence and neuroscience · 2021Article
- Interrogative suggestibility in the elderly.PloS one · 2020Article
- Observational
- Machine Learning Increases Diagnosticity in Psychometric Evaluation of Alexithymia in Fibromyalgia.Frontiers in medicine · 2019Article
- Machine Learning in Psychometrics and Psychological Research.Frontiers in psychology · 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.