AIMC Topic: Adolescent

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Development of artificial neural network model for prediction of post-streptococcus mutans in dental caries.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Streptococcus mutans is the primary initiator and most common organism associated with dental caries. Prediction of post-Streptococcus mutans favours in the selection of appropriate caries excavation method which eventually ...

Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.

JDR clinical and translational research
OBJECTIVES: Evaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral heal...

Cooperation with autonomous machines through culture and emotion.

PloS one
As machines that act autonomously on behalf of others-e.g., robots-become integral to society, it is critical we understand the impact on human decision-making. Here we show that people readily engage in social categorization distinguishing humans ("...

Patients' views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire.

European radiology
OBJECTIVES: The patients' view on the implementation of artificial intelligence (AI) in radiology is still mainly unexplored territory. The aim of this article is to develop and validate a standardized patient questionnaire on the implementation of A...

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia.

BMC medical informatics and decision making
BACKGROUND: The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Altho...

Using machine learning to predict opioid misuse among U.S. adolescents.

Preventive medicine
This study evaluated prediction performance of three different machine learning (ML) techniques in predicting opioid misuse among U.S. adolescents. Data were drawn from the 2015-2017 National Survey on Drug Use and Health (N = 41,579 adolescents, age...

Predicting skilled delivery service use in Ethiopia: dual application of logistic regression and machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Skilled assistance during childbirth is essential to reduce maternal deaths. However, in Ethiopia, which is among the six countries contributing to more than half of the global maternal deaths, the coverage of births attended by skilled h...

Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification.

Computational and mathematical methods in medicine
In recent years, functional brain network topological features have been widely used as classification features. Previous studies have found that network node scale differences caused by different network parcellation definitions significantly affect...