AIMC Topic: Deep Learning
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Food-derived DPP4 inhibitors: Drug discovery based on high-throughput virtual screening and deep learning.
Food chemistry
Feb 21, 2025
Dipeptidyl peptidase-4 (DPP-4) is a critical target for the treatment of type 2 diabetes. This study outlines the development of six compounds derived from food sources and modified to create promising candidates for the treatment of diabetes. These ...
Large-scale benchmarking and boosting transfer learning for medical image analysis.
Medical image analysis
Feb 21, 2025
Transfer learning, particularly fine-tuning models pretrained on photographic images to medical images, has proven indispensable for medical image analysis. There are numerous models with distinct architectures pretrained on various datasets using di...
Hyperfusion: A hypernetwork approach to multimodal integration of tabular and medical imaging data for predictive modeling.
Medical image analysis
Feb 21, 2025
The integration of diverse clinical modalities such as medical imaging and the tabular data extracted from patients' Electronic Health Records (EHRs) is a crucial aspect of modern healthcare. Integrative analysis of multiple sources can provide a com...
Explainability and uncertainty: Two sides of the same coin for enhancing the interpretability of deep learning models in healthcare.
International journal of medical informatics
Feb 21, 2025
BACKGROUND: The increasing use of Deep Learning (DL) in healthcare has highlighted the critical need for improved transparency and interpretability. While Explainable Artificial Intelligence (XAI) methods provide insights into model predictions, reli...
Incorporating indirect MRI information in a CT-based deep learning model for prostate auto-segmentation.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Feb 21, 2025
BACKGROUND AND PURPOSE: Computed tomography (CT) imaging poses challenges for delineation of soft tissue structures for prostate cancer external beam radiotherapy. Guidelines require the input of magnetic resonance imaging (MRI) information. We devel...
Deep learning combined Monte Carlo simulation reveal the fundamental light propagation in apple puree: Monitoring the quality changes from different cultivar, storage period and heating duration.
Food research international (Ottawa, Ont.)
Feb 21, 2025
This work explored the light propagation of purees from a large variability of apple cultivar, storage period and heating duration based on their optical absorption (μ) and reduced scattering (μ') properties at 900-1650 nm, in order to better monitor...
Missing-modality enabled multi-modal fusion architecture for medical data.
Journal of biomedical informatics
Feb 21, 2025
BACKGROUND: Fusion of multi-modal data can improve the performance of deep learning models. However, missing modalities are common in medical data due to patient specificity, which is detrimental to the performance of multi-modal models in applicatio...
Deep learning imputes DNA methylation states in single cells and enhances the detection of epigenetic alterations in schizophrenia.
Cell genomics
Feb 21, 2025
DNA methylation (DNAm) is a key epigenetic mark with essential roles in gene regulation, mammalian development, and human diseases. Single-cell technologies enable profiling DNAm at cytosines in individual cells, but they often suffer from low covera...
Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.
Journal of chemical information and modeling
Feb 21, 2025
Proteins are inherently dynamic, and their conformational ensembles play a crucial role in biological function. Large-scale motions may govern the protein structure-function relationship, and numerous transient but stable conformations of intrinsical...
Explainable paroxysmal atrial fibrillation diagnosis using an artificial intelligence-enabled electrocardiogram.
The Korean journal of internal medicine
Feb 21, 2025
BACKGROUND/AIMS: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent ...
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