AIMC Topic: Machine Learning

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Analysis of ultrasonic vocalizations from mice using computer vision and machine learning.

eLife
Mice emit ultrasonic vocalizations (USVs) that communicate socially relevant information. To detect and classify these USVs, here we describe VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect U...

Artificial Intelligence DENTOMO: Opportunities and Prospects for Interpretation of Cone Beam CT in Dentistry.

Bulletin of experimental biology and medicine
The model of artificial intelligence DENTOMO, which allows automated deciphering the CT in maxillofacial area, was developed and implemented in practical dentistry. The presented model is based on two convolutional neural networks, includes a databas...

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

PloS one
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts fo...

A model based on Bayesian confirmation and machine learning algorithms to aid archaeological interpretation by integrating incompatible data.

PloS one
The interpretation of archaeological features often requires a combined methodological approach in order to make the most of the material record, particularly from sites where this may be limited. In practice, this requires the consultation of differ...

Simulating reference crop evapotranspiration with different climate data inputs using Gaussian exponential model.

Environmental science and pollution research international
Obtaining accurate data on reference crop evapotranspiration (ET) is important for agricultural water management. A novel Gaussian exponential model (GEM) was developed in this study to predict ET with limited climatic data. The GEM was further compa...

Development and Validation of a Radiomics Model for Differentiating Bone Islands and Osteoblastic Bone Metastases at Abdominal CT.

Radiology
Background It is important to diagnose sclerotic bone lesions in order to determine treatment strategy. Purpose To evaluate the diagnostic performance of a CT radiomics-based machine learning model for differentiating bone islands and osteoblastic bo...

Machine Learning Methods to Predict the Terrestrial and Marine Origin of Natural Products.

Molecular informatics
In recent years there has been a growing interest in studying the differences between the chemical and biological space represented by natural products (NPs) of terrestrial and marine origin. In order to learn more about these two chemical spaces, ma...

Machine learning-based analysis of alveolar and vascular injury in SARS-CoV-2 acute respiratory failure.

The Journal of pathology
Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pneumopathy is characterized by a complex clinical picture and heterogeneous pathological lesions, both involving alveolar and vascular components. The severity and distribution of morpholo...

Safety-driven design of machine learning for sepsis treatment.

Journal of biomedical informatics
Machine learning (ML) has the potential to bring significant clinical benefits. However, there are patient safety challenges in introducing ML in complex healthcare settings and in assuring the technology to the satisfaction of the different regulato...

Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning.

Journal of chemical theory and computation
Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially those remote from the active site, alter drug binding to confer resistance are poorly u...