# Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives
## 4 Discussion
Therefore, using probabilistic genotyping software facilitates the control of imported trace samples, particularly those with damaged DNA [75,76]. It also enables the comparison of the presence or absence of alleles in the reference profile and the trace sample directly. Additionally, the availability of software tools reduces analysis time and human weariness [77]. Prior to interpretation, the electropherogram must be inspected to confirm if the profile is indicative of a DNA component or an artifact. There are two ways to go about this phase. When done by hand, it takes a while and can produce different results depending on the analyst reading the layout. To get around this restriction, an analytical threshold--below which the data are discarded--or a double reading method by two separate analysts is used. However, these methods may squander a significant amount of genetic material and require an unnecessary amount of analytical time. However, sophisticated EPG scanning systems like GeneMarker, OSIRIS, and Genemapper may be able to automatically eliminate artifacts. Even with this capability, a lot of artifacts still need to be manually removed before the EPG can be utilized for criminal investigations, which prolongs the reading process. These days, ANNs could be used to create an expert EPG reading system that can discriminate between alleles and artifact, reducing the amount of manual control that is required [48]. Moreover, the application of the latest techniques in forensic DNA profiling that have been established in the last few years employing MPS, also known as NGS, is another crucial question regarding the mixed profile [78]. These techniques can simultaneously identify SNPs, STRs, and in/del (insertions and deletions). Using spatially separated and clonally amplified DNA templates, MPS is related to a range of high-speed sequencing platforms (sometimes referred to as \"second generation\" or \"next generation\") that share a common technical approach to sequence many fragments in parallel [79]. These methods include multiple steps, including library construction, enrichment, and bridge amplification or emulsion PCR. STRs may be amplified and then sequenced; this method allows nucleotide variations found in the flanking regions and repeat motifs of interest to be analyzed. The data produced by these new methods are compatible with previously archived data [80]. Moving forward with MPS will allow the forensic community to continue using millions of DNA profiles that are currently stored in DNA databases, while also expanding its use of forensic DNA typing with increased genetic diversity in STR and SNP. Continued advances in AI are likely to play a crucial role in solving crimes and promoting justice in the future [40,81]. Great progress has been made in other fields of forensic sciences such as forensic odontology. One of the first applications was reported by [PERSON] et al. [19], who described a dental biometric system for human identification using dental radiographs. The described system is based on two main stages: feature extraction and matching. Tooth correspondences between postmortem and anemotern radiographs are established, and a distance based on corresponding teeth measures similarity. The potential applications of artificial intelligence technology in forensic odontology can be categorized into four areas: analysis of human bite marks, identification of sex determination, age estimation, and dental comparison [82]. For example, considering the international migration scenario that is considered a present concern worldwide, determining a minor's age represents an important goal for upholding the rights of all minors [83]. Methods should be replicable, accurate, and objective: in this regard, the use of new AI tools is necessary to guarantee a trustworthy procedure.