AIMC Topic: Algorithms

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An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Digital rectal examination (DRE) is considered a quality metric for prostate cancer care. However, much of the DRE related rich information is documented as free-text in clinical narratives. Therefore, we aimed to develop a natural language processin...

A Scalable Machine Learning Approach for Inferring Probabilistic US-LI-RADS Categorization.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We propose a scalable computerized approach for large-scale inference of Liver Imaging Reporting and Data System (LI-RADS) final assessment categories in narrative ultrasound (US) reports. Although our model was trained on reports created using a LI-...

Using Data Mining To Search for Perovskite Materials with Higher Specific Surface Area.

Journal of chemical information and modeling
The specific surface area (SSA) of ABO-type perovskite is one of the important properties associated with photocatalytic ability. In this work, data mining methods were used to explore the relationship between the SSA (in the range of 1-60 m g) of pe...

Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach.

Molecules (Basel, Switzerland)
Inferring potential adverse drug reactions is an important and challenging task for the drug discovery and healthcare industry. Many previous studies in computational pharmacology have proposed utilizing multi-source drug information to predict drug ...

DoseNet: a volumetric dose prediction algorithm using 3D fully-convolutional neural networks.

Physics in medicine and biology
The goal of this study is to demonstrate the feasibility of a novel fully-convolutional volumetric dose prediction neural network (DoseNet) and test its performance on a cohort of prostate stereotactic body radiotherapy (SBRT) patients. DoseNet is su...

Is Intensity Inhomogeneity Correction Useful for Classification of Breast Cancer in Sonograms Using Deep Neural Network?

Journal of healthcare engineering
The sonogram is currently an effective cancer screening and diagnosis way due to the convenience and harmlessness in humans. Traditionally, lesion boundary segmentation is first adopted and then classification is conducted, to reach the judgment of b...

Combination of high-frequency SSVEP-based BCI and computer vision for controlling a robotic arm.

Journal of neural engineering
OBJECTIVE: Recent attempts in developing brain-computer interface (BCI)-controlled robots have shown the potential of this area in the field of assistive robots. However, implementing the process of picking and placing objects using a BCI-controlled ...

Ensemble Neural Networks (ENN): A gradient-free stochastic method.

Neural networks : the official journal of the International Neural Network Society
In this study, an efficient stochastic gradient-free method, the ensemble neural networks (ENN), is developed. In the ENN, the optimization process relies on covariance matrices rather than derivatives. The covariance matrices are calculated by the e...

Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill.

Environmental science and pollution research international
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environ...