AIMC Topic: Humans

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Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) provides guidelines for risk stratification of lesions detected on multiparametric MRI (mpMRI) of the prostate but suffers from high intra/interreader variability.

Emotion recognition with convolutional neural network and EEG-based EFDMs.

Neuropsychologia
Electroencephalogram (EEG), as a direct response to brain activity, can be used to detect mental states and physical conditions. Among various EEG-based emotion recognition studies, due to the non-linear, non-stationary and the individual difference ...

Borrowing external information to improve Bayesian confidence propagation neural network.

European journal of clinical pharmacology
PURPOSE: A Bayesian confidence propagation neural network (BCPNN) is a signal detection method used by the World Health Organization Uppsala Monitoring Centre to analyze spontaneous reporting system databases. We modify the BCPNN to increase its sens...

Integrative blockwise sparse analysis for tissue characterization and classification.

Artificial intelligence in medicine
The topic of sparse representation of samples in high dimensional spaces has attracted growing interest during the past decade. In this work, we develop sparse representation-based methods for classification of clinical imaging patterns into healthy ...

An artificial intelligence decision support system for the management of type 1 diabetes.

Nature metabolism
Type 1 diabetes (T1D) is characterized by pancreatic beta cell dysfunction and insulin depletion. Over 40% of people with T1D manage their glucose through multiple injections of long-acting basal and short-acting bolus insulin, so-called multiple dai...

Predicting drug-drug interactions using multi-modal deep auto-encoders based network embedding and positive-unlabeled learning.

Methods (San Diego, Calif.)
Drug-drug interactions (DDIs) are crucial for public health and patient safety, which has aroused widespread concern in academia and industry. The existing computational DDI prediction methods are mainly divided into four categories: literature extra...

Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques.

Sensors (Basel, Switzerland)
Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurem...