AIMC Topic: Machine Learning

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Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry-A Systematic Review.

BioMed research international
OBJECTIVE: The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.

Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms.

PloS one
The aims are to improve the efficiency in analyzing the regional economic changes in China's high-tech industrial development zones (IDZs), ensure the industrial structural integrity, and comprehensively understand the roles of capital, technology, a...

ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities.

Journal of chemical information and modeling
Computational methods such as machine learning approaches have a strong track record of success in predicting the outcomes of in vitro assays. In contrast, their ability to predict in vivo endpoints is more limited due to the high number of parameter...

Machine Learning Strategies When Transitioning between Biological Assays.

Journal of chemical information and modeling
Machine learning is widely used in drug development to predict activity in biological assays based on chemical structure. However, the process of transitioning from one experimental setup to another for the same biological endpoint has not been exten...

Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study.

Journal of medical Internet research
BACKGROUND: The Multidimensional Prognostic Index (MPI) is an aggregate, comprehensive, geriatric assessment scoring system derived from eight domains that predict adverse outcomes, including 12-month mortality. However, the prediction accuracy of us...

[Artificial Intelligence in epidemiology].

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Artificial Intelligence can be leveraged to analyze great amounts of data. It can be used on images or textual data to define the epidemiology of diseases, such as cancer. In this review, we will present and discuss the applications of AI in this set...

Machine learning-based analysis of operator pupillary response to assess cognitive workload in clinical ultrasound imaging.

Computers in biology and medicine
INTRODUCTION: Pupillometry, the measurement of eye pupil diameter, is a well-established and objective modality correlated with cognitive workload. In this paper, we analyse the pupillary response of ultrasound imaging operators to assess their cogni...

Utterance Level Feature Aggregation with Deep Metric Learning for Speech Emotion Recognition.

Sensors (Basel, Switzerland)
Emotion is a form of high-level paralinguistic information that is intrinsically conveyed by human speech. Automatic speech emotion recognition is an essential challenge for various applications; including mental disease diagnosis; audio surveillance...

An Improved Vulnerability Exploitation Prediction Model with Novel Cost Function and Custom Trained Word Vector Embedding.

Sensors (Basel, Switzerland)
Successful cyber-attacks are caused by the exploitation of some vulnerabilities in the software and/or hardware that exist in systems deployed in premises or the cloud. Although hundreds of vulnerabilities are discovered every year, only a small frac...

Using a stepwise approach to simultaneously develop and validate machine learning based prediction models.

Journal of clinical epidemiology
Accurate diagnosis of a disease is essential in healthcare. Prediction models, based on classical regression techniques, are widely used in clinical practice. Machine Learning (ML) techniques might be preferred in case of a large amount of data per p...