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Attention-Based MultiOffset Deep Learning Reconstruction of Chemical Exchange Saturation Transfer (AMO-CEST) MRI.
IEEE journal of biomedical and health informatics
Aug 6, 2024
One challenge of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is the long scan time due to multiple acquisitions of images at different saturation frequency offsets. k-space under-sampling strategy is commonly used to...
Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system.
Biosensors & bioelectronics
Aug 3, 2024
Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated...
APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation.
Transplant immunology
Aug 2, 2024
BACKGROUND: Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stres...
GraphPro: An interpretable graph neural network-based model for identifying promoters in multiple species.
Computers in biology and medicine
Aug 2, 2024
Promoters are DNA sequences that bind with RNA polymerase to initiate transcription, regulating this process through interactions with transcription factors. Accurate identification of promoters is crucial for understanding gene expression regulation...
Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence.
ACS chemical neuroscience
Aug 2, 2024
The development of new drugs addressing serious mental health and other disorders should avoid the psychedelic experience. Analogs of psychedelic drugs can have clinical utility and are termed "psychoplastogens". These represent promising candidates ...
A competing risks machine learning study of neutron dose, fractionation, age, and sex effects on mortality in 21,000 mice.
Scientific reports
Aug 2, 2024
This study explores the impact of densely-ionizing radiation on non-cancer and cancer diseases, focusing on dose, fractionation, age, and sex effects. Using historical mortality data from approximately 21,000 mice exposed to fission neutrons, we empl...
Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.
Nature biomedical engineering
Jul 31, 2024
Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membranes. It is therefore central to their therapeutic use that rules governing the membrane selectivity of antimicrobial peptides be deciphered. However,...
Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jul 30, 2024
Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turnover of individual TF binding sites, resulting in cross-species predictive performance being consistently worse than within-species performance. In thi...
Amino acid metabolomics and machine learning-driven assessment of future liver remnant growth after hepatectomy in livers of various backgrounds.
Journal of pharmaceutical and biomedical analysis
Jul 23, 2024
Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with different liver backgrounds is a pressing clinical issue. Amino acid (AA) metabolism plays a crucial role in liver regeneration. In this study, we comb...
Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.
Magnetic resonance in medicine
Jul 19, 2024
PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods.
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