Evidence map›Paper›PMID 37860773›Full record

ReviewiScience2023

Digital forensic intelligence for illicit drug analysis in forensic investigations.

Mayssa Hachem, Rabeb Mizouni, Ibtesam Mohammed Alawadhi, Mohamad J Altamimi

Abstract readReview
In one paragraph

Review in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mayssa HachemDepartment of Chemistry and Healthcare Engineering Innovation Center, Khalifa University of Sciences and Technology, Abu Dhabi P.O. Box 127788, United Arab Emirates.
Rabeb MizouniDepartment of Electrical Engineering and Computer Science, Khalifa University of Sciences and Technology, Abu Dhabi P.O. Box 127788, United Arab Emirates.
Ibtesam Mohammed AlawadhiDubai Police Academy, Dubai P.O. Box 1493, United Arab Emirates.
Mohamad J AltamimiDubai Police, General Department of Forensic Science and Criminology, Drug Surveillance Center, Drug Profiling Section, Dubai P.O. Box 1493, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In forensic investigations, forensic intelligence is required for illicit drug profiling in order to allow police officers and law enforcements to recognize crime developments and adjust their actions. In the present paper, we propose a novel framework for Digital Forensic Drug Intelligence (DFDI) by fusing digital forensic and drug profiling data through intelligent cycles, where a targeted and iterative collection of evidence from diverse sources is a core step in the process of drug profiling. Drug profiling data combined with digital data from seized devices collected, examined, and analyzed will allow authorities to generate valuable information about illicit drug trafficking routes and manufacturing. Such data can be stored in seized illicit drug databases to build in an intelligent way, all findings, hypotheses and recommendations, allowing law enforcement to make decisions. Our framework will potentially provide a better understanding of profiling, trafficking and distribution of illicit drugs.

Indexed as

ChemistryComputer scienceData analysisForensic toxicology

Identifiers

PMID37860773
PMCPMC10582396

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.