AIMC Topic: Algorithms

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Guiding Neuroevolution with Structural Objectives.

Evolutionary computation
The structure and performance of neural networks are intimately connected, and by use of evolutionary algorithms, neural network structures optimally adapted to a given task can be explored. Guiding such neuroevolution with additional objectives rela...

Deep neural networks in psychiatry.

Molecular psychiatry
Machine and deep learning methods, today's core of artificial intelligence, have been applied with increasing success and impact in many commercial and research settings. They are powerful tools for large scale data analysis, prediction and classific...

Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.

Journal of medical Internet research
BACKGROUND: Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening tools, such as Health Risk Appraisal, are restricted in their achievement this goal due to their li...

Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination.

Biomarkers in medicine
AIM: Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.

End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning.

IEEE transactions on pattern analysis and machine intelligence
We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera control signals as output (e.g., move forward, turn left, etc.). Conventional methods tackle tracking an...

Predicting the cytotoxicity of chemicals using ensemble learning methods and molecular fingerprints.

Journal of applied toxicology : JAT
The prediction of compound cytotoxicity is an important part of the drug discovery process. However, it usually appears as poor predictive performance because the datasets are high-throughput and have a class-imbalance problem. In this study, several...

Real-time tracking of surgical instruments based on spatio-temporal context and deep learning.

Computer assisted surgery (Abingdon, England)
ABSTARCT Real-time tool tracking in minimally invasive-surgery (MIS) has numerous applications for computer-assisted interventions (CAIs). Visual tracking approaches are a promising solution to real-time surgical tool tracking, however, many approach...

Application of adaptive-network-based fuzzy inference systems to the parameter optimization of a biochemical rule-based model.

Computers in biology and medicine
In this study, the binding of allergens to antibody-receptor complexes was investigated. This process is important in understanding the allergic response. A BioNetGen model that simulates this process, combined with a novel method for encoding steric...

Artifact correction in low-dose dental CT imaging using Wasserstein generative adversarial networks.

Medical physics
PURPOSE: In recent years, health risks concerning high-dose x-ray radiation have become a major concern in dental computed tomography (CT) examinations. Therefore, adopting low-dose computed tomography (LDCT) technology has become a major focus in th...

Highly accelerated, model-free diffusion tensor MRI reconstruction using neural networks.

Medical physics
PURPOSE: The purpose of this study was to develop a neural network that accurately performs diffusion tensor imaging (DTI) reconstruction from highly accelerated scans.