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Dental Records

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Incorrect identification of a military pilot with international implications.

International journal of legal medicine
The case is reported of a military pilot shot down in 1986 during a mission whose body was recovered in an advanced state of decomposition and delivered to Italian police in 1989. The first autopsy led to an incorrect identification of the corpse. Be...

Identifying Patients' Smoking Status from Electronic Dental Records Data.

Studies in health technology and informatics
Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessib...

Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it's unclear to what extent patient-reported CVD information is accu...

Structuring electronic dental records through deep learning for a clinical decision support system.

Health informatics journal
Extracting information from unstructured clinical text is a fundamental and challenging task in medical informatics. Our study aims to construct a natural language processing (NLP) workflow to extract information from Chinese electronic dental record...

Use GPT-J Prompt Generation with RoBERTa for NER Models on Diagnosis Extraction of Periodontal Diagnosis from Electronic Dental Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study explored the usability of prompt generation on named entity recognition (NER) tasks and the performance in different settings of the prompt. The prompt generation by GPT-J models was utilized to directly test the gold standard as well as t...

Predicting sequenced dental treatment plans from electronic dental records using deep learning.

Artificial intelligence in medicine
BACKGROUND: Designing appropriate clinical dental treatment plans is an urgent need because a growing number of dental patients are suffering from partial edentulism with the population getting older.

A personalized periodontitis risk based on nonimage electronic dental records by machine learning.

Journal of dentistry
OBJECTIVE: This study aimed to develop a machine-learning (ML) model to predict the risk for Periodontal Disease (PD) based on nonimage electronic dental records (EDRs).