AIMC Topic: Humans

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Assessing prospective molecular biomarkers and functional pathways in severe asthma based on a machine learning method and bioinformatics analyses.

The Journal of asthma : official journal of the Association for the Care of Asthma
BACKGROUND: Severe asthma, which differs significantly from typical asthma, involves specific molecular biomarkers that enhance our understanding and diagnostic capabilities. The objective of this study is to assess the biological processes underlyin...

Machine learning assisted rapid approach for quantitative prediction of biochemical parameters of blood serum with FTIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study develops regression models for predicting blood biochemical data using Fourier-transform infrared spectroscopy (FTIR) analysis. Absorption at specific wavelengths of blood serum is revealed to have strong correlations with biochemical para...

Graph based recurrent network for context specific synthetic lethality prediction.

Science China. Life sciences
The concept of synthetic lethality (SL) has been successfully used for targeted therapies. To further explore SL for cancer therapy, identifying more SL interactions with therapeutic potential are essential. Recently, graph neural network-based deep ...

The Future of Oral Oncology: How Artificial Intelligence is Redefining Surgical Procedures and Patient Management.

International dental journal
INTRODUCTION AND AIMS: The future of oral oncology is significantly influenced by the incorporation of artificial intelligence (AI) technologies, such as surgical robotics and early histopathological diagnosis and detection of diseases. This article ...

Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.

Hypertension research : official journal of the Japanese Society of Hypertension
Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound is a typical way to diagnose hypertension-mediated heart change, it often fails to detect early subtle structural changes. Electrocardiogram(ECG) repre...

A machine learning algorithm for creating isotropic 3D aortic segmentations from routine cardiac MR localizers.

Magnetic resonance imaging
BACKGROUND: The identification and measurement of aortic aneurysms is an important clinical problem. While specialized high-resolution 3D CMR sequences allow detailed aortic assessment, they are time-consuming which limits their use in screening rout...

Avoidable biopsies? Validating artificial intelligence-based decision support software in indeterminate thyroid nodules.

Surgery
BACKGROUND: Multiple artificial intelligence (AI) systems have been approved to risk-stratify thyroid nodules through sonographic characterization. We sought to validate the ability of one such AI system, Koios DS (Koios Medical, Chicago, IL), to aid...

Deep Neural Network-Based Accelerated Failure Time Models Using Rank Loss.

Statistics in medicine
An accelerated failure time (AFT) model assumes a log-linear relationship between failure times and a set of covariates. In contrast to other popular survival models that work on hazard functions, the effects of covariates are directly on failure tim...

Data-augmented machine learning scoring functions for virtual screening of YTHDF1 mA reader protein.

Computers in biology and medicine
Machine learning is rapidly advancing the drug discovery process, significantly enhancing speed and efficiency. Innovation in computer-aided drug design is primarily driven by structure- and ligand-based approaches. When the number of known inhibitor...

Identification of key biomarkers for predicting atherosclerosis progression in polycystic ovary syndrome via bioinformatics analysis and machine learning.

Computers in biology and medicine
OBJECTIVE: Polycystic ovary syndrome (PCOS) is one of the most significant cardiovascular risk factors, playing vital roles in various cardiovascular diseases such as atherosclerosis (AS). This study attempted to explore key biomarkers for predicting...