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TRV-2026-0048Version 5 · Retracted

Written 2026-07-12 20:58:05 UTC · current record

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TRUVACE RECORD VERSION
record: TRV-2026-0048
version: 5
kind: retracted
reason: Retracted from the live record
timestamp: 2026-07-12T20:58:05.990515Z
status: archived
lens: g_space
sector: health
headline: Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
dek: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications. More importantly, DL has outperformed well-known ML techniques in many domains, e.g., cybersecurity, natural language processing, bioinformatics, robotics and control, and medical information processing, among many others. Despite it has been contributed several works reviewing the State-of-the-Art on …
gain_reading: More importantly, DL has outperformed well-known ML techniques in many domains, e.g., cybersecurity, natural language processing, bioinformatics, robotics and control, and medical information processing, among many others.
problem_reading: (none)
limitation: Historical research candidate. An editor must verify study design, population, effect size, and whether later evidence changes the reading before publication.
tag: Evidence-backed gain
key_points: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. | Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. | One of the benefits of DL is the ability to learn massive amounts of data.
rundown: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance.

One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications.
sources:
- peer_reviewed | Applied Sciences | https://doi.org/10.3390/app15073898 | 2025-04-02
- peer_reviewed | Artificial Intelligence Review | https://doi.org/10.1007/s10462-023-10466-8 | 2023-04-17
- peer_reviewed | Journal of Big Data | https://doi.org/10.1186/s40537-021-00444-8 | 2021-03-31
- peer_reviewed | Software | https://doi.org/10.3390/software4030014 | 2025-06-28
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