Evidence map›Paper›PMID 41393458›Full record

ArticleBioinformation2025

Artificial intelligence for dental implant classification and peri-implant disease detection: A clinical study.

Gousia Shafat Khan, Syed Aaliyah, Sunil Pal, Rahul Tiwari, Smitha M, Heena Dixit, Prashant M C, Thoid Ali

Abstract read
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In one paragraph

Article in Bioinformation, 2025. 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

8 authors.

Gousia Shafat KhanDepartment of Prosthodontics, Crown & Bridge, Government Dental College and Hospital Srinagar, Srinagar, Jammu and Kashmir, India.
Syed AaliyahDepartment of Prosthodontics, Crown & Bridge, Government Dental College and Hospital Srinagar, Srinagar, Jammu and Kashmir, India.
Sunil PalDepartment of Prosthodontics, ITS Dental College, Ghaziabad, Uttar Pradesh, India.
Rahul TiwariDepartment of Oral and Maxillofacial Surgery, RKDF Dental College and Research Centre, Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India.
Smitha MDepartment of Prosthodontics, NSVK SV Dental College, Bengaluru, Karnataka, India.
Heena DixitCommisionerate of Health and Family Welfare, Government of Telangana, Hyderabad, India.
Prashant M CDepartment of Oral and Maxillofacial Surgery, RKDF Dental College and Research Centre, Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India.
Thoid AliDepartment of Oral and Maxillofacial Surgery, RKDF Dental College and Research Centre, Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is transforming diagnostic accuracy in dental care, particularly in the field of implantology. A prospective research was conducted on 150 patients with 212 previously placed dental implants. The AI system correctly classified 97.2% of implants, with a sensitivity of 96.3% and specificity of 98.0%. For peri-implant disease detection, the system achieved 91.8% sensitivity and 93.4% specificity, with an overall AUC-ROC of 0.94. AI demonstrates high diagnostic performance in both implant classification and peri-implant disease detection.

Indexed as

Artificial intelligencedeep learningdental implantsdiagnostic imagingperi-implantitis

Identifiers

PMID41393458
PMCPMC12697519

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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.