AIMC Topic: Algorithms

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Efficient automated detection of mitotic cells from breast histological images using deep convolution neutral network with wavelet decomposed patches.

Computers in biology and medicine
In medical practice, the mitotic cell count from histological images acts as a proliferative marker for cancer diagnosis. Therefore, an accurate method for detecting mitotic cells in histological images is essential for cancer screening. Manual evalu...

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Nature genetics
Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consumin...

A Predictive Model for Guillain-Barré Syndrome Based on Ensemble Methods.

Computational intelligence and neuroscience
Nowadays, Machine Learning methods have proven to be highly effective on the identification of various types of diseases, in the form of predictive models. Guillain-Barré syndrome (GBS) is a potentially fatal autoimmune neurological disorder that has...

A Novel Classification and Identification Scheme of Emitter Signals Based on Ward's Clustering and Probabilistic Neural Networks with Correlation Analysis.

Computational intelligence and neuroscience
The rapid development of modern communication technology makes the identification of emitter signals more complicated. Based on Ward's clustering and probabilistic neural networks method with correlation analysis, an ensemble identification algorithm...

Sensor Information Fusion by Integrated AI to Control Public Emotion in a Cyber-Physical Environment.

Sensors (Basel, Switzerland)
The cyber-physical system (CPS) is a next-generation smart system that combines computing with physical space. It has been applied in various fields because the uncertainty of the physical world can be ideally controlled using cyber technology. In te...

Deep Learning-Based Algorithms in Screening of Diabetic Retinopathy: A Systematic Review of Diagnostic Performance.

Ophthalmology. Retina
TOPIC: Diagnostic performance of deep learning-based algorithms in screening patients with diabetes for diabetic retinopathy (DR). The algorithms were compared with the current gold standard of classification by human specialists.

Accelerating deep learning with memcomputing.

Neural networks : the official journal of the International Neural Network Society
Restricted Boltzmann machines (RBMs) and their extensions, often called "deep-belief networks", are powerful neural networks that have found applications in the fields of machine learning and artificial intelligence. The standard way to train these m...

ProvCaRe: Characterizing scientific reproducibility of biomedical research studies using semantic provenance metadata.

International journal of medical informatics
OBJECTIVE: Reproducibility of research studies is key to advancing biomedical science by building on sound results and reducing inconsistencies between published results and study data. We propose that the available data from research studies combine...

A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning.

Journal of medical systems
Skeletal bone age assessment is a widely used standard procedure in both disease detection and growth prediction for children in endocrinology. Conventional manual assessment methods mainly rely on personal experience in observing X-ray images of lef...

Unsupervised Feature Extraction via Deep Learning for Histopathological Classification of Colon Tissue Images.

IEEE transactions on medical imaging
Histopathological examination is today's gold standard for cancer diagnosis. However, this task is time consuming and prone to errors as it requires a detailed visual inspection and interpretation of a pathologist. Digital pathology aims at alleviati...