AI Medical Compendium Journal:
Frontiers in bioscience (Landmark edition)

Showing 1 to 10 of 24 articles

Machine learning paradigm for dynamic contrast-enhanced MRI evaluation of expanding bladder.

Frontiers in bioscience (Landmark edition)
Delineation of the bladder under a dynamic contrast enhanced (DCE)-MRI protocol requires robust segmentation. However, this method is subject to errors due to variations in the content of fluid within the bladder, as well as presence of air and simil...

An AI-based approach in determining the effect of meteorological factors on incidence of malaria.

Frontiers in bioscience (Landmark edition)
This study presents the classification of malaria-prone zones based on (a) meteorological factors, (b) demographics and (c) patient information. Observations are performed on extended features in dataset over the spiking and non-spiking classifiers i...

State-of-the-art methods in healthcare text classification system: AI paradigm.

Frontiers in bioscience (Landmark edition)
Machine learning has shown its importance in delivering healthcare solutions and revolutionizing the future of filtering huge amountd of textual content. The machine intelligence can adapt semantic relations among text to infer finer contextual infor...

A new backpropagation neural network classification model for prediction of incidence of malaria.

Frontiers in bioscience (Landmark edition)
Malaria is an infectious disease caused by parasitic protozoans of the Plasmodium family. These parasites are transmitted by mosquitos which are common in certain parts of the world. Based on their specific climates, these regions have been classifie...

State-of-the-art review on deep learning in medical imaging.

Frontiers in bioscience (Landmark edition)
Deep learning (DL) is affecting each and every sphere of public and private lives and becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the activities of neurons in the neocortex of human brain where the thought...

Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network.

Frontiers in bioscience (Landmark edition)
Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of AD with a deep 3D Convolutional Neural Network (3D-CNN), which can show generic features capturing A...

DTC-m6Am: A Framework for Recognizing N6,2'-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms.

Frontiers in bioscience (Landmark edition)
BACKGROUND: mAm is a specific RNA modification that plays an important role in regulating mRNA stability, translational efficiency, and cellular stress response. mAm's precise identification is essential to gain insight into its functional mechanisms...

Machine Learning Reveals Aneuploidy Characteristics in Cancers: The Impact of BEX4.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Aneuploidy is crucial yet under-explored in cancer pathogenesis. Specifically, the involvement of brain expressed X-linked gene 4 () in microtubule formation has been identified as a potential aneuploidy mechanism. Nevertheless, 's compre...

Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL).

Frontiers in bioscience (Landmark edition)
In this comprehensive review, we delve into the transformative role of artificial intelligence (AI) in refining the application of multi-omics and spatial multi-omics within the realm of diffuse large B-cell lymphoma (DLBCL) research. We scrutinized ...

Deep-Learning Uncovers certain CCM Isoforms as Transcription Factors.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Cerebral Cavernous Malformations (CCMs) are brain vascular abnormalities associated with an increased risk of hemorrhagic strokes. Familial CCMs result from autosomal dominant inheritance involving three genes: (), (), and (). CCM1 and...