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Artificial intelligence in forensic neuropathology: A systematic review

Medicina e Tecnologia
Imagem de arquivo, ilustrativa — não é do estudo. Nervo em corte transversal ao microscópio óptico. Berkshire Community College Bioscience Image Library · CC0 · Wikimedia Commons

Revisão sistemáticaNível 1 · Evidência consolidadaJournal of forensic and legal medicine7 ago 20256 citações

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Resumo original em inglês

O que aconteceu

In recent years, Artificial Intelligence (AI) has gained prominence as a robust tool for clinical decision-making and diagnostics, owing to its capacity to process and analyze large datasets with high accuracy. More specifically, Deep Learning, and its subclasses, have shown significant potential in image processing, including medical imaging and histological analysis. In forensic pathology, AI has been employed for the interpretation of histopathological data, identifying conditions such as myocardial infarction, traumatic injuries, and heart rhythm abnormalities. This review aims to highlight key advances in AI's role, particularly machine learning (ML) and deep learning (DL) techniques, in forensic neuropathology, with a focus on its ability to interpret instrumental and histopathological data to support professional diagnostics.

A systematic review of the literature regarding applications of Artificial Intelligence in forensic neuropathology was carried out according to the Preferred Reporting Item for Systematic Review (PRISMA) standards. We selected 34 articles regarding the main applications of AI in this field, dividing them into two categories: those addressing traumatic brain injury (TBI), including intracranial hemorrhage or cerebral microbleeds, and those focusing on epilepsy and SUDEP, including brain disorders and central nervous system neoplasms capable of inducing seizure activity.

O que encontraram

In both cases, the application of AI techniques demonstrated promising results in the forensic investigation of cerebral pathology, providing a valuable computer-assisted diagnostic tool to aid in post-mortem computed tomography (PMCT) assessments of cause of death and histopathological analyses.

Por que isso importa

In conclusion, this paper presents a comprehensive overview of the key neuropathology areas where the application of artificial intelligence can be valuable in investigating causes of death.

Resumo publicado sob licença CC BY. A tradução para o português ainda não chegou a este estudo.

O estudo original

Artificial intelligence in forensic neuropathology: A systematic review

Michele Treglia, Raffaele La Russa, Gabriele Napoletano, Alessandro Ghamlouch, Fabio Del Duca, Biancamaria Treves, Paola Frati, Aniello Maiese

Descritores MeSH

  • Artificial Intelligence
  • Neuropathology
  • Forensic Pathology
  • Humans
  • Epilepsy
  • Machine Learning
  • Deep Learning

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