AIMC Topic: Machine Learning

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Morphological classification of odontogenic keratocysts using Bouligand-Minkowski fractal descriptors.

Computers in biology and medicine
The Odontogenic keratocyst (OKC) is a cystic lesion of the jaws, which has high growth and recurrence rates compared to other cysts of the jaws (for instance, radicular cyst, which is the most common jaw cyst type). For this reason OKCs are considere...

Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Measurement of stride-related, biomechanical parameters is the common rationale for objective gait impairment scoring. State-of-the-art double-integration approaches to extract these parameters from inertial sensor data are, however, limited in their...

A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series.

IEEE journal of biomedical and health informatics
Physiological variables, such as heart rate (HR), blood pressure (BP) and respiration (RESP), are tightly regulated and coupled under healthy conditions, and a break-down in the coupling has been associated with aging and disease. We present an appro...

Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System.

ACS combinatorial science
Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial X-ray diffraction data sets, which we address by develo...

Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry.

NeuroImage. Clinical
This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortical thickness measurements, volumetric measurements, hippocampal shape, and hippocampal texture). The ...

Multisource Transfer Learning With Convolutional Neural Networks for Lung Pattern Analysis.

IEEE journal of biomedical and health informatics
Early diagnosis of interstitial lung diseases is crucial for their treatment, but even experienced physicians find it difficult, as their clinical manifestations are similar. In order to assist with the diagnosis, computer-aided diagnosis systems hav...

Multichannel Convolutional Neural Network for Biological Relation Extraction.

BioMed research international
The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are suscep...

Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility in a Single Descriptor.

Journal of chemical information and modeling
A new molecular descriptor, nConf, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular...

Resistance gene identification from Larimichthys crocea with machine learning techniques.

Scientific reports
The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. ...

Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility.

Proteins
Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality a...