AIMC Topic: Machine Learning

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Predicting the Assisted Living Care Needs Using Machine Learning and Health State Survey Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Effective pain management can significantly improve quality of life and outcomes for various types of patients (e.g. elderly, adult, young) and often requires assisted living for a significant number of people worldwide. In order to improve our under...

Assisting the Non-invasive Diagnosis of Liver Fibrosis Stages using Machine Learning Methods.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fibrosis is a significant indication of chronic liver diseases often due to hepatitis C Virus. It is becoming a global concern as a result of the rapid increase in the number of HCV infected patients, the high cost and flaws associated with the asses...

Evaluating the Predictability of Cancer Types from 536 Somatic Mutations: A New Dataset.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, we introduce a new dataset for cancer research containing somatic mutation states of 536 genes of the Cancer Gene Census (CGC). We used somatic mutation information from the Cancer Genome Atlas (TCGA) projects to create this dataset. A...

An Empirical Method of Automatic Pattern Extraction for Clinical Text Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Clinical text classification is an indispensable and extensively studied problem in medical text processing. Existing research primarily employs machine learning and pattern based approaches to address the stated problem. In general, pattern based ap...

Practical Machine Learning-Based Sepsis Prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sepsis is a life-threatening clinical syndrome and one of the most expensive conditions treated in hospitals. It is challenging to detect due to the nonspecific clinical signs and the absence of gold standard diagnostics. However, early recognition o...

Machine Learning and Deep Neural Network Architectures for 3D Motion Capture Datasets.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Biomechanical movement data are highly correlated multivariate time-series for which a variety of machine learning and deep neural network classification techniques are possible. For image classification, convolutional neural networks have reshaped t...

A Machine Learning Approach to Detecting Low Medication State with Wearable Technologies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Medication adherence is a critical component and implicit assumption of the patient life cycle that is often violated, incurring financial and medical costs to both patients and the medical system at large. As obstacles to medication adherence are co...

Visualizing Worklog Based on Human Working Activity Recognition Using Unsupervised Activity Pattern Encoding.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Wearable motion sensor-based complex activity recognition during working hours has recently been studied to evaluate and thereby improve worker productivity. In the application of this technique to practical fields, one of the biggest challenges is p...

Prediction of atherosclerotic disease progression combining computational modelling with machine learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Non-invasive serial computed tomography coronary angiography (CTCA) was acquired from 32 patients and 3D reconstruction of 58 coronary arteries was achieved. The arterial geometries were utilized for blood flow and LDL transport modelling. Navier-Sto...

Schrödinger Spectrum Based PPG Features for the Estimation of the Arterial Blood Pressure.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, photoplethysmogram (PPG) features are combined with supervised machine learning algorithms to estimate arterial blood pressure (ABP). Three algorithms for the estimation of cuffless ABP using PPG signals are compared. Since PPG signals...