AIMC Topic: Algorithms

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Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach.

Ultrasound in medicine & biology
The discrimination between benign and malignant adnexal masses in ultrasound images represents one of the most challenging problems in gynecologic practice. In the study described here, a new method for automatic discrimination of adnexal masses base...

EffectorP: predicting fungal effector proteins from secretomes using machine learning.

The New phytologist
Eukaryotic filamentous plant pathogens secrete effector proteins that modulate the host cell to facilitate infection. Computational effector candidate identification and subsequent functional characterization delivers valuable insights into plant-pat...

Finite-time stabilization control for discontinuous time-delayed networks: New switching design.

Neural networks : the official journal of the International Neural Network Society
This paper discusses the finite-time stabilization problem for time-varying delayed neural networks (DNNs) with discontinuous activation functions. By using fixed point theory and set-valued analysis, we establish the existence theorem of equilibrium...

Effect of edge pruning on structural controllability and observability of complex networks.

Scientific reports
Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex...

Logic regression-derived algorithms for syndromic management of vaginal infections.

BMC medical informatics and decision making
BACKGROUND: Syndromic management of vaginal infections is known to have poor diagnostic accuracy. Logic regression is a machine-learning procedure which allows for the identification of combinations of variables to predict an outcome, such as the pre...

Automatic Estimation of Osteoporotic Fracture Cases by Using Ensemble Learning Approaches.

Journal of medical systems
Ensemble learning methods are one of the most powerful tools for the pattern classification problems. In this paper, the effects of ensemble learning methods and some physical bone densitometry parameters on osteoporotic fracture detection were inves...

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching.

IEEE transactions on medical imaging
Automatic and reliable segmentation of the prostate is an important but difficult task for various clinical applications such as prostate cancer radiotherapy. The main challenges for accurate MR prostate localization lie in two aspects: (1) inhomogen...

Quantifying co-cultured cell phenotypes in high-throughput using pixel-based classification.

Methods (San Diego, Calif.)
Biologists increasingly use co-culture systems in which two or more cell types are grown in cell culture together in order to better model cells' native microenvironments. Co-cultures are often required for cell survival or proliferation, or to maint...