SynthesisInternational journal of environmental research and public health2022
Machine Learning and Criminal Justice: A Systematic Review of Advanced Methodology for Recidivism Risk Prediction.
Synthesis in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed, 63 citations in OpenAlex.
- Predicting criminal offence in adolescents who exhibit antisocial behaviour: a machine learning study using data from a large randomised controlled trial of multisystemic therapy.European child & adolescent psychiatry · 2025Trial
- Inter-rater reproducibility in medico-legal injury assessment: a pilot study with an exploratory comparison to a large language model.International journal of legal medicine · 2026Article
- AI-assisted rational decision-making.Synthese · 2026Article
- Article
- A fairness scale for real-time recidivism forecasts using a national database of convicted offenders.Neural computing & applications · 2025Article
- When do drugs trigger criminal behavior? a machine learning analysis of offenders and non-offenders with schizophrenia and comorbid substance use disorder.Frontiers in psychiatry · 2024Article
- Beyond Discrimination: Generative AI Applications and Ethical Challenges in Forensic Psychiatry.Frontiers in psychiatry · 2024Review
- Using machine learning to forecast domestic homicide via police data and super learning.Scientific reports · 2023Article
- Editorial: Equitable digital medicine and home health care.Frontiers in public health · 2023Article
- Model Building in Forensic Psychiatry: A Machine Learning Approach to Screening Offender Patients with SSD.Diagnostics (Basel, Switzerland) · 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
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent evolution in the field of data science has revealed the potential utility of machine learning (ML) applied to criminal justice. Hence, the literature focused on finding better techniques to predict criminal recidivism risk is rapidly flourishing. However, it is difficult to make a state of the art for the application of ML in recidivism prediction. In this systematic review, out of 79 studies from Scopus and PubMed online databases we selected, 12 studies that guarantee the replicability of the models across different datasets and their applicability to recidivism prediction. The different datasets and ML techniques used in each of the 12 studies have been compared using the two selected metrics. This study shows how each method applied achieves good performance, with an average score of 0.81 for ACC and 0.74 for AUC. This systematic review highlights key points that could allow criminal justice professionals to routinely exploit predictions of recidivism risk based on ML techniques. These include the presence of performance metrics, the use of transparent algorithms or explainable artificial intelligence (XAI) techniques, as well as the high quality of input data.
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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.