AIMC Topic: Machine Learning

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Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
UNLABELLED: Background Stratification of cardiovascular risk in patients with ischemic stroke is important as it may inform management strategies. We aimed to develop a machine-learning-derived prognostic model for the prediction of cardiovascular ri...

Privacy preserving distributed learning classifiers - Sequential learning with small sets of data.

Computers in biology and medicine
BACKGROUND: Artificial intelligence (AI) typically requires a significant amount of high-quality data to build reliable models, where gathering enough data within a single institution can be particularly challenging. In this study we investigated the...

A deep learning based ensemble learning method for epileptic seizure prediction.

Computers in biology and medicine
In epilepsy, patients suffer from seizures which cannot be controlled with medicines or surgical treatments in more than 30% of the cases. Prediction of epileptic seizures is extremely important so that they can be controlled with medication before t...

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning.

Biomolecules
Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and d...

LPWAN and Embedded Machine Learning as Enablers for the Next Generation of Wearable Devices.

Sensors (Basel, Switzerland)
The penetration of wearable devices in our daily lives is unstoppable. Although they are very popular, so far, these elements provide a limited range of services that are mostly focused on monitoring tasks such as fitness, activity, or health trackin...

Explainable Anomaly Detection Framework for Maritime Main Engine Sensor Data.

Sensors (Basel, Switzerland)
In this study, we proposed a data-driven approach to the condition monitoring of the marine engine. Although several unsupervised methods in the maritime industry have existed, the common limitation was the interpretation of the anomaly; they do not ...

Machine learning in medicine: a practical introduction to natural language processing.

BMC medical research methodology
BACKGROUND: Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. Natural language processing (NLP) describes a set of techniques used to convert passages of wri...

Machine learning predicts 3D printing performance of over 900 drug delivery systems.

Journal of controlled release : official journal of the Controlled Release Society
Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy trial-and-error approach in optimizati...

FEA and Machine Learning Techniques for Hidden Structure Analysis.

Sensors (Basel, Switzerland)
This study focuses on investigating and predicting two hidden structures: plant root system architecture and non-visible bubbles in plexiglass. Current approaches are damaging, expensive, or time-consuming. Infrared imaging was used to study the root...