AI Medical Compendium Journal:
Physiological genomics

Showing 1 to 5 of 5 articles

Artificial intelligence and omics in malignant gliomas.

Physiological genomics
Glioblastoma multiforme (GBM) is one of the most common and aggressive type of malignant glioma with an average survival time of 12-18 mo. Despite the utilization of extensive surgical resections using cutting-edge neuroimaging, and advanced chemothe...

Implementation of convolutional neural network approach for COVID-19 disease detection.

Physiological genomics
In this paper, two novel, powerful, and robust convolutional neural network (CNN) architectures are designed and proposed for two different classification tasks using publicly available data sets. The first architecture is able to decide whether a gi...

Machine learning-based classification and diagnosis of clinical cardiomyopathies.

Physiological genomics
Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical...

Artificial intelligence, physiological genomics, and precision medicine.

Physiological genomics
Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an ...