AIMC Topic: Models, Biological

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Spine morphology and energetics: how principles from nature apply to robotics.

Bioinspiration & biomimetics
Inspired by the locomotive advantages that an articulated spine enables in quadrupedal animals, we explore and quantify the energetic effect that an articulated spine has in legged robots. We compare two model instances of a conceptual planar quadrup...

Predicting urinary tract infections in the emergency department with machine learning.

PloS one
BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine culture, part of the gold standard for diagnosis of UTI, is usually not available for 24-48 hours aft...

Comorbidity Scoring with Causal Disease Networks.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, there has been numerous studies constructing a disease network with diverse sources of data. Many researchers attempted to extend the usage of the disease network by employing machine learning algorithms on various problems such as p...

Noninvasive detection of macrophage activation with single-cell resolution through machine learning.

Proceedings of the National Academy of Sciences of the United States of America
We present a method enabling the noninvasive study of minute cellular changes in response to stimuli, based on the acquisition of multiple parameters through label-free microscopy. The retrieved parameters are related to different attributes of the c...

TLBO-Based Adaptive Neurofuzzy Controller for Mobile Robot Navigation in a Strange Environment.

Computational intelligence and neuroscience
This work investigates the possibility of using a novel evolutionary based technique as a solution for the navigation problem of a mobile robot in a strange environment which is based on Teaching-Learning-Based Optimization. TLBO is employed to train...

Prediction of Overall Survival and Novel Classification of Patients with Gastric Cancer Using the Survival Recurrent Network.

Annals of surgical oncology
BACKGROUND: Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients.

Prediction of rupture risk in anterior communicating artery aneurysms with a feed-forward artificial neural network.

European radiology
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).

Bipedal robotic walking control derived from analysis of human locomotion.

Biological cybernetics
This paper proposes the design of a bipedal robotic controller where the function between the sensory input and motor output is treated as a black box derived from human data. In order to achieve this, we investigated the causal relationship between ...

Quantitative approaches to energy and glucose homeostasis: machine learning and modelling for precision understanding and prediction.

Journal of the Royal Society, Interface
Obesity is a major global public health problem. Understanding how energy homeostasis is regulated, and can become dysregulated, is crucial for developing new treatments for obesity. Detailed recording of individual behaviour and new imaging modaliti...