AIMC Topic: Deep Learning

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HDXRank: A Deep Learning Framework for Ranking Protein Complex Predictions with Hydrogen-Deuterium Exchange Data.

Journal of chemical theory and computation
Accurate modeling of protein-protein complex structures is essential for understanding biological mechanisms. Hydrogen-deuterium exchange (HDX) experiments provide valuable insights into binding interfaces. Incorporating HDX data into protein complex...

Deep learning for echocardiographic assessment and risk stratification of aortic, mitral, and tricuspid regurgitation: the DELINEATE-regurgitation study.

European heart journal
BACKGROUND AND AIMS: Classification and risk stratification in aortic (AR), mitral (MR), and tricuspid regurgitation (TR) remains a significant clinical challenge. This study aimed to develop an artificial intelligence (AI) system to assess valvular ...

ModiDeC: a multi-RNA modification classifier for direct nanopore sequencing.

Nucleic acids research
RNA modifications play a crucial role in various cellular functions. Here, we present ModiDeC, a deep-learning-based classifier able to identify and distinguish multiple RNA modifications (N6-methyladenosine, inosine, pseudouridine, 2'-O-methylguanos...

Computer vision techniques for high-speed atomic force microscopy of DNA molecules.

Nanotechnology
High-speed atomic force microscopy (HSAFM) can produce thousands of topographic, nanoscale images over a small area. One emerging application of this technique is the detection and sizing of single DNA molecules derived from biological experiments an...

Automatic contour quality assurance using deep-learning based contours.

Physics in medicine and biology
Safe deployment of auto-contouring models requires the inclusion of automated quality assurance (QA). One such approach is to use two independent auto-contouring models and compare them geometrically for acceptability. This is not effective because g...

MSCMLCIDTI: Drug-Target Interaction Prediction Based on Multiscale Feature Extraction and Deep Interactive Attention Fusion Mechanisms.

Journal of computational chemistry
Drug-target interaction prediction serves as a crucial component in accelerating drug discovery. To overcome current limitations in deep learning approaches, specifically the inadequate representation of local features and insufficient modeling of dr...

MS2MP: A Deep Learning Framework for Metabolic Pathway Prediction from MS/MS-Based Untargeted Metabolomics.

Analytical chemistry
MS/MS-based untargeted metabolomics generates complex data, but pathway enrichment analysis is constrained by the low annotation rates of metabolic features. Here, we propose MS2MP, a novel deep learning-based framework for KEGG pathway prediction di...

Dose-aware denoising diffusion model for low-dose CT.

Physics in medicine and biology
Low-dose computed tomography (LDCT) denoising plays an important role in medical imaging for reducing the radiation dose to patients. Recently, various data-driven and diffusion-based deep learning (DL) methods have been developed and shown promising...

Deep learning-based contour propagation in magnetic resonance imaging-guided radiotherapy of lung cancer patients.

Physics in medicine and biology
Fast and accurate organ-at-risk (OAR) and gross tumor volume (GTV) contour propagation methods are needed to improve the efficiency of magnetic resonance (MR) imaging-guided radiotherapy. We trained deformable image registration networks to accuratel...

A robust automated segmentation method for white matter hyperintensity of vascular-origin.

NeuroImage
White matter hyperintensity (WMH) is a primary manifestation of small vessel disease (SVD), leading to vascular cognitive impairment and other disorders. Accurate WMH quantification is vital for diagnosis and prognosis, but current automatic segmenta...