AIMC Topic: Machine Learning

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Development and validation of a fully automated 2-dimensional imaging system generating body condition scores for dairy cows using machine learning.

Journal of dairy science
Monitoring body condition score (BCS) is a useful management tool to estimate the energy reserves of an individual cow or a group of cows. The aim of this study was to develop and evaluate the performance of a fully automated 2-dimensional imaging sy...

Identifying keystone species in microbial communities using deep learning.

Nature ecology & evolution
Previous studies suggested that microbial communities can harbour keystone species whose removal can cause a dramatic shift in microbiome structure and functioning. Yet, an efficient method to systematically identify keystone species in microbial com...

N-of-one differential gene expression without control samples using a deep generative model.

Genome biology
Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can...

Applying Machine Learning Analysis Based on Proximal Femur of Abdominal Computed Tomography to Screen for Abnormal Bone Mass in Femur.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate the performance of machine learning analysis based on proximal femur of abdominal computed tomography (CT) scans in screening for abnormal bone mass in femur.

Machine learning for microbiologists.

Nature reviews. Microbiology
Machine learning is increasingly important in microbiology where it is used for tasks such as predicting antibiotic resistance and associating human microbiome features with complex host diseases. The applications in microbiology are quickly expandin...

Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review.

Accident; analysis and prevention
Accurately modelling crashes, and predicting crash occurrence and associated severities are a prerequisite for devising countermeasures and developing effective road safety management strategies. To this end, crash prediction modelling using machine ...

Connecting the dots towards precision orthodontics.

Orthodontics & craniofacial research
Precision orthodontics entails the use of personalized clinical, biological, social and environmental knowledge of each patient for deep individualized clinical phenotyping and diagnosis combined with the delivery of care using advanced customized de...

Development and performance comparison of optimized machine learning-based regression models for predicting energy-related carbon dioxide emissions.

Environmental science and pollution research international
Accurate prediction of CO emissions for the countries has become a crucial task in decision-making processes for planning energy conversion and usage, supporting the design of effective emissions reduction strategies, and helping to achieve the goal ...

Evaluating the chaos game representation of proteins for applications in machine learning models: prediction of antibody affinity and specificity as a case study.

Journal of molecular modeling
CONTEXT: Machine learning techniques are becoming increasingly important in the selection and optimization of therapeutic molecules, as well as for the selection of formulation components and the prediction of long-term stability. Compared to first-p...

On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers.

Scientific reports
An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such an ensemble can outperform the single best classifier. If so, what form of ens...