AIMC Topic: Models, Biological

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Machine Learning Readmission Risk Modeling: A Pediatric Case Study.

BioMed research international
BACKGROUND: Hospital readmission prediction in pediatric hospitals has received little attention. Studies have focused on the readmission frequency analysis stratified by disease and demographic/geographic characteristics but there are no predictive ...

Machine Learning Analysis of Matricellular Proteins and Clinical Variables for Early Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage.

Molecular neurobiology
Although delayed cerebral ischemia (DCI) is a well-known complication after subarachnoid hemorrhage (SAH), there are no reliable biomarkers to predict DCI development. Matricellular proteins (MCPs) have been reported relevant to DCI and expected to b...

Improving the Antinoise Ability of DNNs via a Bio-Inspired Noise Adaptive Activation Function Rand Softplus.

Neural computation
Although deep neural networks (DNNs) have led to many remarkable results in cognitive tasks, they are still far from catching up with human-level cognition in antinoise capability. New research indicates how brittle and susceptible current models are...

Dynamic multi-outcome prediction after injury: Applying adaptive machine learning for precision medicine in trauma.

PloS one
OBJECTIVE: Machine learning techniques have demonstrated superior discrimination compared to conventional statistical approaches in predicting trauma death. The objective of this study is to evaluate whether machine learning algorithms can be used to...

Vision-Based Robot Navigation through Combining Unsupervised Learning and Hierarchical Reinforcement Learning.

Sensors (Basel, Switzerland)
Extensive studies have shown that many animals' capability of forming spatial representations for self-localization, path planning, and navigation relies on the functionalities of place and head-direction (HD) cells in the hippocampus. Although there...

Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network.

Food research international (Ottawa, Ont.)
The expected increase of global obesity prevalence makes it necessary to have information about the effects of meal intakes on the feeling of appetite. Because human clinical studies are time and cost intensive, there is a need for a reliable alterna...

LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features.

BMC cancer
BACKGROUND: Lung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction...

Swarm-Fuzzy Rule-Based Targeted Nano Delivery Using Bioinspired Nanomachines.

IEEE transactions on nanobioscience
Cooperative navigation and swarm decision making take center stage in a broad range of distributed applications with high-environmental and measurement uncertainties. Here, we propose a fuzzy carotid body-inspired nanonetwork (FCBN) of autonomous nan...

Prediction of aptamer-protein interacting pairs based on sparse autoencoder feature extraction and an ensemble classifier.

Mathematical biosciences
Aptamer-protein interacting pairs play important roles in physiological functions and structural characterization. Identifying aptamer-protein interacting pairs is challenging and limited, despite of the tremendous applications of aptamers. Therefore...

Design and demonstration of a bio-inspired flapping-wing-assisted jumping robot.

Bioinspiration & biomimetics
Jumping insects such as fleas, froghoppers, grasshoppers, and locusts take off from the ground using a catapult mechanism to push their legs against the surface of the ground while using their pairs of flapping wings to propel them into the air. Such...