AIMC Topic: Models, Biological

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An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases.

Interdisciplinary sciences, computational life sciences
Malaria is one of the epidemics that can cause human death. Accurate and rapid diagnosis of malaria is important for treatment. Due to the limited number of data and human factors, the prediction performance and reliability of traditional classificat...

Developing a novel force forecasting technique for early prediction of critical events in robotics.

PloS one
Safety critical events in robotic applications can often be characterized by forces between the robot end-effector and the environment. One application in which safe interaction between the robot and environment is critical is in the area of medical ...

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Cell
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are ...

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Scientific reports
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 20...

Decentralized control of insect walking: A simple neural network explains a wide range of behavioral and neurophysiological results.

PLoS computational biology
Controlling the six legs of an insect walking in an unpredictable environment is a challenging task, as many degrees of freedom have to be coordinated. Solutions proposed to deal with this task are usually based on the highly influential concept that...

Prediction of Intracranial Aneurysm Risk using Machine Learning.

Scientific reports
An efficient method for identifying subjects at high risk of an intracranial aneurysm (IA) is warranted to provide adequate radiological screening guidelines and effectively allocate medical resources. We developed a model for pre-diagnosis IA predic...

Combination of an Artificial Intelligence Approach and Laser Tweezers Raman Spectroscopy for Microbial Identification.

Analytical chemistry
Raman spectroscopy is a nondestructive, label-free, highly specific approach that provides the chemical information on materials. Thus, it is suitable to be used as an effective analytical tool to characterize biological samples. Here we introduce a ...

Key components of mechanical work predict outcomes in robotic stroke therapy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots...