AIMC Topic: Algorithms

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Machine Learning techniques in breast cancer prognosis prediction: A primary evaluation.

Cancer medicine
More than 750 000 women in Italy are surviving a diagnosis of breast cancer. A large body of literature tells us which characteristics impact the most on their prognosis. However, the prediction of each disease course and then the establishment of a ...

Pedestrian Navigation Method Based on Machine Learning and Gait Feature Assistance.

Sensors (Basel, Switzerland)
In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve th...

Predicting pregnancy test results after embryo transfer by image feature extraction and analysis using machine learning.

Scientific reports
Assessing the viability of a blastosyst is still empirical and non-reproducible nowadays. We developed an algorithm based on artificial vision and machine learning (and other classifiers) that predicts pregnancy using the beta human chorionic gonadot...

The detection of age groups by dynamic gait outcomes using machine learning approaches.

Scientific reports
Prevalence of gait impairments increases with age and is associated with mobility decline, fall risk and loss of independence. For geriatric patients, the risk of having gait disorders is even higher. Consequently, gait assessment in the clinics has ...

Climate-induced thermoregulatory responses in a non-linear thermal environment: investigating the inter-dependencies using a facile artificial neural network-based predictive strategy.

International journal of occupational safety and ergonomics : JOSE
. Given the burgeoning impacts of climatic variability on human health, suitable computational paradigms are used to explore the subsequent ergonomic repercussions. The artificial neural network (ANN), in particular, exhibits near-accurate input-outp...

A Noninvasive Glucose Monitoring SoC Based on Single Wavelength Photoplethysmography.

IEEE transactions on biomedical circuits and systems
Conventional glucose monitoring methods for the growing numbers of diabetic patients around the world are invasive, painful, costly and, time-consuming. Complications aroused due to the abnormal blood sugar levels in diabetic patients have created th...

Molecular and DNA Artificial Neural Networks via Fractional Coding.

IEEE transactions on biomedical circuits and systems
This article considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using f...

An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding.

Scientific reports
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline dec...

Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps.

Scientific reports
Cryo-electron microscopy (cryo-EM) has become a leading technology for determining protein structures. Recent advances in this field have allowed for atomic resolution. However, predicting the backbone trace of a protein has remained a challenge on a...

Deep learning models for electrocardiograms are susceptible to adversarial attack.

Nature medicine
Electrocardiogram (ECG) acquisition is increasingly widespread in medical and commercial devices, necessitating the development of automated interpretation strategies. Recently, deep neural networks have been used to automatically analyze ECG tracing...