AIMC Topic: Machine Learning

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Crack Detection in Images of Masonry Using CNNs.

Sensors (Basel, Switzerland)
While there is a significant body of research on crack detection by computer vision methods in concrete and asphalt, less attention has been given to masonry. We train a convolutional neural network (CNN) on images of brick walls built in a laborator...

A Machine Learning Tool Using Digital Microscopy (Morphogo) for the Identification of Abnormal Lymphocytes in the Bone Marrow.

Acta cytologica
Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological disease. The conventional analysis of bone marrow smears is performed under a manual microscope, which is labor-intensive and subject to interobserver va...

Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

PloS one
Accuracy of infrared (IR) models to measure soil particle-size distribution (PSD) depends on soil preparation, methodology (sedimentation, laser), settling times and relevant soil features. Compositional soil data may require log ratio (ilr) transfor...

Prioritization of disease genes from GWAS using ensemble-based positive-unlabeled learning.

European journal of human genetics : EJHG
A primary challenge in understanding disease biology from genome-wide association studies (GWAS) arises from the inability to directly implicate causal genes from association data. Integration of multiple-omics data sources potentially provides impor...

Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.

Molecular diversity
Neurological disorders affect various aspects of life. Finding drugs for the central nervous system is a very challenging and complex task due to the involvement of the blood-brain barrier, P-glycoprotein, and the drug's high attrition rates. The ava...

Real Time Multipurpose Smart Waste Classification Model for Efficient Recycling in Smart Cities Using Multilayer Convolutional Neural Network and Perceptron.

Sensors (Basel, Switzerland)
Urbanization is a big concern for both developed and developing countries in recent years. People shift themselves and their families to urban areas for the sake of better education and a modern lifestyle. Due to rapid urbanization, cities are facing...

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models.

Journal of Korean medical science
BACKGROUND: We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning...

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

IEEE journal of translational engineering in health and medicine
Blood pressure (BP) is an essential indicator for human health and is known to be greatly influenced by lifestyle factors, like activity and sleep factors. However, the degree of impact of each lifestyle factor on BP is unknown and may vary between ...

Collaborative driving style classification method enabled by majority voting ensemble learning for enhancing classification performance.

PloS one
The classification of driving styles plays a fundamental role in evaluating drivers' driving behaviors, which is of great significance to traffic safety. However, it still suffers from various challenges, including the insufficient accuracy of the mo...