AIMC Topic: Machine Learning

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An Intelligent and Reliable Hyperparameter Optimization Machine Learning Model for Early Heart Disease Assessment Using Imperative Risk Attributes.

Journal of healthcare engineering
Heart disease is a severe disorder, which inflicts an adverse burden on all societies and leads to prolonged suffering and disability. We developed a risk evaluation model based on visible low-cost significant noninvasive attributes using hyperparame...

Machine Learning-Aided Chronic Kidney Disease Diagnosis Based on Ultrasound Imaging Integrated with Computer-Extracted Measurable Features.

Journal of digital imaging
Although ultrasound plays an important role in the diagnosis of chronic kidney disease (CKD), image interpretation requires extensive training. High operator variability and limited image quality control of ultrasound images have made the application...

Conformational Sampling for Transition State Searches on a Computational Budget.

Journal of chemical theory and computation
Transition state searches are the basis for computationally characterizing reaction mechanisms, making them a pivotal tool in myriad chemical applications. Nevertheless, common search algorithms are sensitive to reaction conformations, and the confor...

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.

Journal of biomedical informatics
BACKGROUND: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among various decision-making models to determine the degree of disease deterioration at the bedside. AutoScore was proposed as a useful ...

Simple, fast, and flexible framework for matrix completion with infinite width neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Matrix completion problems arise in many applications including recommendation systems, computer vision, and genomics. Increasingly larger neural networks have been successful in many of these applications but at considerable computational costs. Rem...

Sensor Fault Diagnostics Using Physics-Informed Transfer Learning Framework.

Sensors (Basel, Switzerland)
The field of smart health monitoring, intelligent fault detection and diagnosis is expanding dramatically in order to maintain successful operation in many engineering applications. Considering possible fault scenarios that can occur in a system, ind...

Prognostics of unsupported railway sleepers and their severity diagnostics using machine learning.

Scientific reports
Railway sleepers are safety-critical components of a railway structure. They support ballasted track superstructure and are a critical factor in track geometry and track components' deterioration. Unsupported sleepers are a common issue incurred afte...

Hyperspectral retrievals of suspended sediment using cluster-based machine learning regression in shallow waters.

The Science of the total environment
Remote sensing of suspended sediment in shallow waters is challenging because of the increased optical variability of the water, resulting from the influence of suspended matter in the water column and the heterogeneous bottom properties. To overcome...

Design and Implementation of an ML and IoT Based Adaptive Traffic-Management System for Smart Cities.

Sensors (Basel, Switzerland)
The rapid growth in the number of vehicles has led to traffic congestion, pollution, and delays in logistic transportation in metropolitan areas. IoT has been an emerging innovation, moving the universe towards automated processes and intelligent man...