AIMC Topic: Machine Learning

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Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions.

Protein and peptide letters
The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to det...

Analysis of Collagen Spatial Structure Using Multiphoton Microscopy and Machine Learning Methods.

Biochemistry. Biokhimiia
Pathogenesis of many diseases is associated with changes in the collagen spatial structure. Traditionally, the 3D structure of collagen in biological tissues is analyzed using histochemistry, immunohistochemistry, magnetic resonance imaging, and X-ra...

Iterative image reconstruction for sparse-view CT via total variation regularization and dictionary learning.

Journal of X-ray science and technology
Recently, low-dose computed tomography (CT) has become highly desirable due to the increasing attention paid to the potential risks of excessive radiation of the regular dose CT. However, ensuring image quality while reducing the radiation dose in th...

Reduced iteration image reconstruction of incomplete projection CT using regularization strategy through Lp norm dictionary learning.

Journal of X-ray science and technology
BACKGROUND: For sparse and limited angle projection Computed Tomography (CT), the reconstructed image usually suffers from considerable artifacts due to undersampled data.

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification.

Journal of Alzheimer's disease : JAD
BACKGROUND: Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient manage...

Dynamic Features Impact on the Quality of Chronic Heart Failure Predictive Modelling.

Studies in health technology and informatics
We study the way dynamics affects modelling in chronic heart failure (CHF) tasks. By dynamics we understand the patient history and the appearance of new events, states and variables changing in time. The goal is to understand what impact past data h...

Using Machine Learning for Personalized Patient Adherence Level Determination.

Studies in health technology and informatics
The paper deals with using a machine-learning algorithm for patient adherence level determination. For this purpose, we developed a neural network using the Python language, Keras library, and PyCharm platform. We analyzed different medical data coll...

Echocardiography Population Study in Russian Federation for 4P Medicine Using Machine Learning.

Studies in health technology and informatics
This article describes the study results of echocardiographic (ECHO) test data for 4P medicine applied to cardiovascular patients. Data from more than 145,000 echocardiographic tests were analyzed. One of the objectives of the study is the possibilit...