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Mesterséges intelligencia a törvényszéki tudományokban Revolúció vagy invázió? I. rész

Authors: Márton Lontai; Horolma Pamzsav; Dávid Petrétei;

Mesterséges intelligencia a törvényszéki tudományokban Revolúció vagy invázió? I. rész

Abstract

Aim: The first half of the two-part study is on the emerging role of artificial intelligence in the forensic sciences. After clarifying the basic concepts and a brief historical overview, the possibilities of using AI in various forensic fields are discussed: genetics, pattern recognition, chemistry, toxicology, anthropology, forensic medicine, and scene reconstruction. Methodology: The study synthesises several recently published international papers. Findings: The penetration of the application of artificial intelligence into some fields of science is undoubtedly an ongoing process. Most of the varied forensic fields also cannot avoid this development. Analysing large databases unmanageable with traditional methods, pattern recognition, and machine learning can all be important tools for forensic science. However, an important conclusion is that AI is a supporter of human expert work, not a substitute. Value: In the field of forensic sciences, no such detailed summary article has been published in Hungarian so far.

Keywords

fizikai antropológia, forenzikus tudományok, RA1001 Forensic Medicine. Medical jurisprudence. Legal medicine / igazságügyi-, QH426 Genetics / genetika, 610, HV6001-HV6030 Criminology / kriminalisztika, GN Anthropology / embertan, forenzikus tudomány, antropológia, genetika, JF20-2112, mesterséges intelligencia, Political institutions and public administration (General), örökléstan, törvényszéki orvostan

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold