AIMC Topic: Algorithms

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BrainMRNet: Brain tumor detection using magnetic resonance images with a novel convolutional neural network model.

Medical hypotheses
A brain tumor is a mass that grows unevenly in the brain and directly affects human life. This mass occurs spontaneously because of the tissues surrounding the brain or the skull. Surgical methods are generally preferred for the treatment of the brai...

Brain Tumor Detection by Using Stacked Autoencoders in Deep Learning.

Journal of medical systems
Brain tumor detection depicts a tough job because of its shape, size and appearance variations. In this manuscript, a deep learning model is deployed to predict input slices as a tumor (unhealthy)/non-tumor (healthy). This manuscript employs a high p...

Representation learning for clinical time series prediction tasks in electronic health records.

BMC medical informatics and decision making
BACKGROUND: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, n...

Combining deep learning and 3D contrast source inversion in MR-based electrical properties tomography.

NMR in biomedicine
Magnetic resonance electrical properties tomography (MR-EPT) is a technique used to estimate the conductivity and permittivity of tissues from MR measurements of the transmit magnetic field. Different reconstruction methods are available; however, al...

Prediction of Skin Disease with Three Different Feature Selection Techniques Using Stacking Ensemble Method.

Applied biochemistry and biotechnology
Skin disease is the most common problem between people. Due to pollution and deployment of ozone layer, harmful UV rays of sun burn the skin and develop various types of skin diseases. Nowadays, machine learning and deep learning algorithms are gener...

Deep Learning Classification of Neuro-Emotional Phase Domain Complexity Levels Induced by Affective Video Film Clips.

IEEE journal of biomedical and health informatics
In the present article, a novel emotional complexity marker is proposed for classification of discrete emotions induced by affective video film clips. Principal Component Analysis (PCA) is applied to full-band specific phase space trajectory matrix (...

Artificial intelligence in medical imaging.

Magnetic resonance imaging
The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how medical imaging is deployed. Artificial intelligence (AI) is potentially another such developmen...

Calibration: the Achilles heel of predictive analytics.

BMC medicine
BACKGROUND: The assessment of calibration performance of risk prediction models based on regression or more flexible machine learning algorithms receives little attention.

Multiple Compounds Recognition from The Tandem Mass Spectral Data Using Convolutional Neural Network.

Molecules (Basel, Switzerland)
Mixtures analysis can provide more information than individual components. It is important to detect the different compounds in the real complex samples. However, mixtures are often disturbed by impurities and noise to influence the accuracy. Purific...

Particle Swarm Optimized Hybrid Kernel-Based Multiclass Support Vector Machine for Microarray Cancer Data Analysis.

BioMed research international
Determining an optimal decision model is an important but difficult combinatorial task in imbalanced microarray-based cancer classification. Though the multiclass support vector machine (MCSVM) has already made an important contribution in this field...