AIMC Topic: Models, Biological

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Machine learning models predicting multidrug resistant urinary tract infections using "DsaaS".

BMC bioinformatics
BACKGROUND: The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine L...

A soft pneumatic bistable reinforced actuator bioinspired by Venus Flytrap with enhanced grasping capability.

Bioinspiration & biomimetics
Soft actuators, as an important part of soft robotics, have attracted significant attention due to their inherent compliance, flexibility and safety. However, low capacity in force and load limits their applications. Prestored elastic energy can impr...

A bio-inspired robotic fish utilizes the snap-through buckling of its spine to generate accelerations of more than 20g.

Bioinspiration & biomimetics
Inspired by the fastest observed live fishes, we have designed, built and tested a robotic fish that emulates the fast-start maneuver of these fishes and generates acceleration and velocity magnitudes comparable to those of the live fishes within the...

Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network.

BioMed research international
Polycystic ovary syndrome (PCOS) is one of the most common metabolic and reproductive endocrinopathies. However, few studies have tried to develop a diagnostic model based on gene biomarkers. In this study, we applied a computational method by combin...

Machine learning-based mortality rate prediction using optimized hyper-parameter.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The current scenario of the Pandemic of COVID-19 demands multi-channel investigations and predictions. A variety of prediction models are available in the literature. The majority of these models are based on extrapolating b...

Bolus pharmacokinetics: moving beyond mass-based dosing to guide drug administration.

Journal of pharmacokinetics and pharmacodynamics
Despite the common approach of bolus drug dosing using a patient's mass, a more tailored approach would be to use empirically derived pharmacokinetic models. Previously, this could only be possible though the use of computer simulation using programs...

Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models.

Journal of medical Internet research
BACKGROUND: The inherent difficulty of identifying and monitoring emerging outbreaks caused by novel pathogens can lead to their rapid spread; and if left unchecked, they may become major public health threats to the planet. The ongoing coronavirus d...

Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.

Computer methods in biomechanics and biomedical engineering
In order to have research on the deformation characteristics and mechanical properties of human red blood cells (RBCs), finite element models of RBC optical tweezers stretching and atomic force microscope (AFM) indentation were established. Non-linea...

Mathematical models and deep learning for predicting the number of individuals reported to be infected with SARS-CoV-2.

Journal of the Royal Society, Interface
We introduce a novel methodology for predicting the time evolution of the number of individuals in a given country reported to be infected with SARS-CoV-2. This methodology, which is based on the synergy of explicit mathematical formulae and deep lea...

Predicting Gram-Positive Bacterial Protein Subcellular Location by Using Combined Features.

BioMed research international
There are a lot of bacteria in the environment, and Gram-positive bacteria are the most common ones. Some Gram-positive bacteria are very harmful to the human body, so it is significant to predict Gram-positive bacterial protein subcellular location....