AIMC Topic: Humans

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Leveraging public AI tools to explore systems biology resources in mathematical modeling.

NPJ systems biology and applications
Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are ...

Machine learning for predicting severe dengue in Puerto Rico.

Infectious diseases of poverty
BACKGROUND: Distinguishing between non-severe and severe dengue is crucial for timely intervention and reducing morbidity and mortality. World Health Organization (WHO)-recommended warning signs offer a practical approach for clinicians but have limi...

Synthetic CT generation from CBCT and MRI using StarGAN in the Pelvic Region.

Radiation oncology (London, England)
RATIONALE AND OBJECTIVES: This study evaluated StarGAN, a deep learning model designed to generate synthetic computed tomography (sCT) images from magnetic resonance imaging (MRI) and cone-beam computed tomography (CBCT) data using a single model. Th...

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.

Journal of translational medicine
The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to precisely cleave problematic regions within DNA sequences. This groundbreaking technology holds immense potential for the development of targeted ther...

Quantifying the tumour vasculature environment from CD-31 immunohistochemistry images of breast cancer using deep learning based semantic segmentation.

Breast cancer research : BCR
BACKGROUND: Tumour vascular density assessed from CD-31 immunohistochemistry (IHC) images has previously been shown to have prognostic value in breast cancer. Current methods to measure vascular density, however, are time-consuming, suffer from high ...

Automated orthodontic diagnosis via self-supervised learning and multi-attribute classification using lateral cephalograms.

Biomedical engineering online
BACKGROUND: Malocclusion, characterized by dental misalignment and improper occlusal relationships, significantly impacts oral health and daily functioning, with a global prevalence of 56%. Lateral cephalogram is a crucial diagnostic tool in orthodon...

Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults utilizing SHAP: a study based on NHANES 2015-2018.

BMC public health
BACKGROUND: Alveolar bone loss (ABL) is common in modern society. Heavy metal exposure is usually considered to be a risk factor for ABL. Some studies revealed a positive trend found between urinary heavy metals and periodontitis using multiple logis...

Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper.

BMC medical informatics and decision making
Training machine learning models using data from severe COVID-19 patients admitted to a central hospital, where entire wards are specifically dedicated to COVID-19, may yield predictions that differ significantly from those generated using data colle...

UTR-Insight: integrating deep learning for efficient 5' UTR discovery and design.

BMC genomics
The 5' UTR is critical for mRNA stability and translation efficiency in therapeutics. We developed UTR-Insight, a model integrating a pretrained language model with a CNN-Transformer architecture, explaining 89.1% of the mean ribosome load (MRL) vari...

Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.

BMC medical imaging
BACKGROUND: Computed tomography attenuation correction (CTAC) is commonly used in cardiac SPECT imaging to reduce soft-tissue attenuation artifacts. However, CTAC is prone to inaccuracies due to CT artifacts and SPECT-CT mismatch, along with addition...