AIMC Topic: Humans

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Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

Genomics
This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neu...

Development and validation of a two-stage convolutional neural network algorithm for segmentation of MRI white matter hyperintensities for longitudinal studies in CADASIL.

Computers in biology and medicine
BACKGROUND: Segmentation of white matter hyperintensities (WMH) in CADASIL, one of the most severe cerebral small vessel disease of genetic origin, is challenging.

Brain-GCN-Net: Graph-Convolutional Neural Network for brain tumor identification.

Computers in biology and medicine
BACKGROUND: The intersection of artificial intelligence and medical image analysis has ushered in a new era of innovation and changed the landscape of brain tumor detection and diagnosis. Correct detection and classification of brain tumors based on ...

The revolution of metaverse in surgery: a mini-review with video.

Updates in surgery
The virtual reality (VR) is an application in which people can interact each other with their own avatars. Metaverse has already been tested in numerous medical fields and health care as telemedicine, second opinion and remote discussion, but in surg...

Could machine learning revolutionize how we treat immune thrombocytopenia?

British journal of haematology
The absence of reliable biomarkers in immune thrombocytopenia (ITP) complicates treatment choice, necessitating a trial-and-error approach. Machine learning (ML) holds promise for transforming ITP treatment by analysing complex data to identify predi...

Single-detector multiplex imaging flow cytometry for cancer cell classification with deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged as a powerful tool for cell analysis in various biomedical fields such as cancer detection. In this study, we develop multiplex imaging flow cytometry...

Identifying psychological predictors of SARS-CoV-2 vaccination: A machine learning study.

Vaccine
BACKGROUND: Major barriers to addressing SARS-CoV-2 vaccine hesitancy include limited knowledge of what causes delay/refusal of SARS-CoV-2 vaccination and limited ability to predict who will remain unvaccinated over significant time periods despite v...

GCGACNN: A Graph Neural Network and Random Forest for Predicting Microbe-Drug Associations.

Biomolecules
The interaction between microbes and drugs encompasses the sourcing of pharmaceutical compounds, microbial drug degradation, the development of , and the impact of on host drug metabolism and immune modulation. These interactions significantly impac...