AIMC Topic: Machine Learning

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Context encoder transfer learning approaches for retinal image analysis.

Computers in biology and medicine
During the last years, deep learning techniques have emerged as powerful alternatives to solve biomedical image analysis problems. However, the training of deep neural networks usually needs great amounts of labeled data to be done effectively. This ...

Conceptual Structure and Current Trends in Artificial Intelligence, Machine Learning, and Deep Learning Research in Sports: A Bibliometric Review.

International journal of environmental research and public health
Artificial intelligence and its subcategories of machine learning and deep learning are gaining increasing importance and attention in the context of sports research. This has also meant that the number of corresponding publications has become comple...

Effective Prediction and Important Counseling Experience for Perceived Helpfulness of Social Question and Answering-Based Online Counseling: An Explainable Machine Learning Model.

Frontiers in public health
The social question answering based online counseling (SQA-OC) is easy access for people seeking professional mental health information and service, has become the crucial pre-consultation and application stage toward online counseling. However, ther...

Advanced machine learning algorithms to evaluate the effects of the raw ingredients on flowability and compressive strength of ultra-high-performance concrete.

PloS one
The estimation of concrete characteristics through artificial intelligence techniques is come out to be an effective way in the construction sector in terms of time and cost conservation. The manufacturing of Ultra-High-Performance Concrete (UHPC) is...

Machine Learning Model for Chest Radiographs: Using Local Data to Enhance Performance.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
PURPOSE: To develop and assess the performance of a machine learning model which screens chest radiographs for 14 labels, and to determine whether fine-tuning the model on local data improves its performance. Generalizability at different institution...

A systematic review of state-of-the-art strategies for machine learning-based protein function prediction.

Computers in biology and medicine
New drug discovery is inseparable from the discovery of drug targets, and the vast majority of the known targets are proteins. At the same time, proteins are essential structural and functional elements of living cells necessary for the maintenance o...

Application of machine learning on understanding biomolecule interactions in cellular machinery.

Bioresource technology
Machine learning (ML) applications have become ubiquitous in all fields of research including protein science and engineering. Apart from protein structure and mutation prediction, scientists are focusing on knowledge gaps with respect to the molecul...

Opportunities and challenges of machine learning in bioprocesses: Categorization from different perspectives and future direction.

Bioresource technology
Recent advances in machine learning (ML) have revolutionized an extensive range of research and industry fields by successfully addressing intricate problems that cannot be resolved with conventional approaches. However, low interpretability and inco...

Ensemble learning based assessment of the role of transcription factors in gene expression.

Computers in biology and medicine
Cancer cells are formed when the associated, active genes fail to function the way they are meant to function. Multiple genes collectively control cell growth by activating a proper set of genes. Regulation of gene expression is controlled through th...