ReviewDiagnostics (Basel, Switzerland)2023
Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine.
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Comparative evaluation of artificial intelligence-deep learning-based cine short-axis segmentation and manual post-processing for left ventricular function and structure in cardiac magnetic resonance.Quantitative imaging in medicine and surgery · 2026Article
- Estimating the Post-Mortem Interval Under Extreme Heat Environments: A Climate-Adaptive Case Series Based on Artificial Intelligence-Supported Diagnostics.Diagnostics (Basel, Switzerland) · 2026Article
- Predicting Physical Appearance from Low Template: State of the Art and Future Perspectives.Genes · 2026Review
- Carbon quantum dots (CQDs) in forensic investigations: a review of current applications and future perspectives.RSC advances · 2025Review
- Emerging Imaging Technologies in Forensic Medicine: A Systematic Review of Innovations, Ethical Challenges, and Future Directions.Diagnostics (Basel, Switzerland) · 2025Review
- AI-Based Predictive Models for Cardiogenic Shock in STEMI: Real-World Data for Early Risk Assessment and Prognostic Insights.Journal of clinical medicine · 2025Article
- Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.Journal of clinical medicine · 2025Article
- Microbial genomics: a potential toolkit for forensic investigations.Forensic science, medicine, and pathology · 2025Review
- Deep learning and firearm wound classification: a pilot study.Frontiers in medicine · 2025Article
- The application of artificial intelligence in forensic pathology: a systematic literature review.Frontiers in medicine · 2025Review
- Diagnostic Challenges in Uncommon Firearm Injury Cases: A Multidisciplinary Approach.Diagnostics (Basel, Switzerland) · 2024Article
- Diagnostic Applications of AI in Sports: A Comprehensive Review of Injury Risk Prediction Methods.Diagnostics (Basel, Switzerland) · 2024Review
- Exploring the Practical Applications of Artificial Intelligence, Deep Learning, and Machine Learning in Maxillofacial Surgery: A Comprehensive Analysis of Published Works.Bioengineering (Basel, Switzerland) · 2024Article
- Future Horizons: The Potential Role of Artificial Intelligence in Cardiology.Journal of personalized medicine · 2024Review
- Sensors in the Detection of Abused Substances in Forensic Contexts: A Comprehensive Review.Micromachines · 2023Review
- A review on artificial intelligence for the diagnosis of fractures in facial trauma imaging.Frontiers in artificial intelligence · 2023Review
- Human Experts and AI Models in Offender Risk Assessment: A Comparative Pilot Study Using the HCR-20V3.Behavioral sciences & the lawArticle
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
Abstract
backgroundThe integration of artificial intelligence (AI) into various fields has ushered in a new era of multidisciplinary progress. Defined as the ability of a system to interpret external data, learn from it, and adapt to specific tasks, AI is poised to revolutionize the world. In forensic medicine and pathology, algorithms play a crucial role in data analysis, pattern recognition, anomaly identification, and decision making. This review explores the diverse applications of AI in forensic medicine, encompassing fields such as forensic identification, ballistics, traumatic injuries, postmortem interval estimation, forensic toxicology, and more.
resultsA thorough review of 113 articles revealed a subset of 32 papers directly relevant to the research, covering a wide range of applications. These included forensic identification, ballistics and additional factors of shooting, traumatic injuries, post-mortem interval estimation, forensic toxicology, sexual assaults/rape, crime scene reconstruction, virtual autopsy, and medical act quality evaluation. The studies demonstrated the feasibility and advantages of employing AI technology in various facets of forensic medicine and pathology.
conclusionsThe integration of AI in forensic medicine and pathology offers promising prospects for improving accuracy and efficiency in medico-legal practices. From forensic identification to post-mortem interval estimation, AI algorithms have shown the potential to reduce human subjectivity, mitigate errors, and provide cost-effective solutions. While challenges surrounding ethical considerations, data security, and algorithmic correctness persist, continued research and technological advancements hold the key to realizing the full potential of AI in forensic applications. As the field of AI continues to evolve, it is poised to play an increasingly pivotal role in the future of forensic medicine and pathology.
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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.