AIMC Topic: Databases, Factual

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Updated Prediction of Aggregators and Assay-Interfering Substructures in Food Compounds.

Journal of agricultural and food chemistry
Positive outcomes in biochemical and biological assays of food compounds may appear due to the well-described capacity of some compounds to form colloidal aggregates that adsorb proteins, resulting in their denaturation and loss of function. This phe...

Cataract Disease Detection by Using Transfer Learning-Based Intelligent Methods.

Computational and mathematical methods in medicine
One of the most common visual disorders is cataracts, which people suffer from as they get older. The creation of a cloud on the lens of our eyes is known as a cataract. Blurred vision, faded colors, and difficulty seeing in strong light are the main...

Prediction of Blood-Brain Barrier Penetration (BBBP) Based on Molecular Descriptors of the Free-Form and In-Blood-Form Datasets.

Molecules (Basel, Switzerland)
The blood-brain barrier (BBB) controls the entry of chemicals from the blood to the brain. Since brain drugs need to penetrate the BBB, rapid and reliable prediction of BBB penetration (BBBP) is helpful for drug development. In this study, free-form ...

A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.

PLoS computational biology
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Computational and mathematical methods in medicine
Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health cris...

RFARN: Retinal vessel segmentation based on reverse fusion attention residual network.

PloS one
Accurate segmentation of retinal vessels is critical to the mechanism, diagnosis, and treatment of many ocular pathologies. Due to the poor contrast and inhomogeneous background of fundus imaging and the complex structure of retinal fundus images, th...

Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data.

Computational and mathematical methods in medicine
The COVID-19 pandemic has had a devastating effect on many people, creating severe anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations against coronavirus, people's feelings have become more diverse and complex. ...

Sound Source Localization Using a Convolutional Neural Network and Regression Model.

Sensors (Basel, Switzerland)
In this research, a novel sound source localization model is introduced that integrates a convolutional neural network with a regression model (CNN-R) to estimate the sound source angle and distance based on the acoustic characteristics of the intera...

Automatic Searching and Pruning of Deep Neural Networks for Medical Imaging Diagnostic.

IEEE transactions on neural networks and learning systems
The field of medical imaging diagnostic makes use of a modality of imaging tests, e.g., X-rays, ultrasounds, computed tomographies, and magnetic resonance imaging, to assist physicians with the diagnostic of patients' illnesses. Due to their state-of...

Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

Scientific reports
We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models ...