AIMC Topic: Artificial Intelligence

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Artificial Intelligence-Based Quantitative Structure-Property Relationship Model for Predicting Human Intestinal Absorption of Compounds with Serotonergic Activity.

Molecular pharmaceutics
Oral medicines represent the largest pharmaceutical market area. To achieve a therapeutic effect, a drug must penetrate the intestinal walls, the main absorption site for orally delivered active pharmaceutical ingredients (APIs). Indeed, predicting d...

Machine learning prediction of mortality in Acute Myocardial Infarction.

BMC medical informatics and decision making
BACKGROUND: Acute Myocardial Infarction (AMI) is the leading cause of death in Portugal and globally. The present investigation created a model based on machine learning for predictive analysis of mortality in patients with AMI upon admission, using ...

Daily reference evapotranspiration prediction for irrigation scheduling decisions based on the hybrid PSO-LSTM model.

PloS one
The shortage of available water resources and climate change are major factors affecting agricultural irrigation. In order to improve the irrigation water use efficiency, it is necessary to predict the water requirements for crops in advance. Referen...

Review: The prevailing mathematical modeling classifications and paradigms to support the advancement of sustainable animal production.

Animal : an international journal of animal bioscience
Mathematical modeling is typically framed as the art of reductionism of scientific knowledge into an arithmetical layout. However, most untrained people get the art of modeling wrong and end up neglecting it because modeling is not simply about writi...

Standardizing analysis of intra-tumoral heterogeneity with computational pathology.

Genes, chromosomes & cancer
Many malignant cancers like glioblastoma are highly adaptive diseases that dynamically change their regional biology to survive and thrive under diverse microenvironmental and therapeutic pressures. While the concept of intra-tumoral heterogeneity ha...

Introduction to artificial intelligence and deep learning using interactive electronic programming notebooks.

Archiv der Pharmazie
Artificial intelligence (AI), or deep learning (DL), approaches have already found their way into our everyday lives. Furthermore, these methods are a central part of research in the life and natural sciences and have been applied in the form of mach...

Digital Histopathology by Infrared Spectroscopic Imaging.

Annual review of analytical chemistry (Palo Alto, Calif.)
Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy w...

Facilitating deep learning through preprocessing of optical coherence tomography images.

BMC ophthalmology
BACKGROUND: While deep learning has delivered promising results in the field of ophthalmology, the hurdle to complete a deep learning study is high. In this study, we aim to facilitate small scale model trainings by exploring the role of preprocessin...

Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness.

Scientific reports
There is a growing piece of evidence that artificial intelligence may be helpful in the entire prostate cancer disease continuum. However, building machine learning algorithms robust to inter- and intra-radiologist segmentation variability is still a...