AIMC Topic: Oligopeptides
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Synthesizing [F]PSMA-1007 PET bone images from CT images with GAN for early detection of prostate cancer bone metastases: a pilot validation study.
BMC cancer
May 21, 2025
BACKGROUND: [F]FDG PET/CT scan combined with [F]PSMA-1007 PET/CT scan is commonly conducted for detecting bone metastases in prostate cancer (PCa). However, it is expensive and may expose patients to more radiation hazards. This study explores deep l...
The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
May 1, 2025
This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep learning (DL) in [F]FDG and [Ga]Ga-prostate-specific membrane antigen (PSMA) PET/CT scans. We used 489 ...
Dynamics and Machine Learning Reveal the Link between Tripeptide Sequences and Evaporation-Driven Material Properties.
Nano letters
Apr 27, 2025
Previous research showed that a peptide composed of three tyrosines (YYY) can turn into organic glass and cause strong adhesion between substrates via evaporation. However, the mechanisms of these processes remain unclear, and the exploration of appl...
Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [F]PSMA-1007 PET/CT and multiparametric MRI.
European journal of nuclear medicine and molecular imaging
Feb 19, 2025
PURPOSE: Accurate prediction of adverse pathology (AP) in prostate cancer (PCa) patients is crucial for formulating effective treatment strategies. This study aims to develop and evaluate a multimodal deep learning model based on [F]PSMA-1007 PET/CT ...
Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning-Based Information Bottleneck.
Journal of chemical theory and computation
Nov 26, 2024
The weighted ensemble (WE) method stands out as a widely used segment-based sampling technique renowned for its rigorous treatment of kinetics. The WE framework typically involves initially mapping the configuration space onto a low-dimensional colle...
Evaluation of the prostate cancer and its metastases in the [ 68 Ga]Ga-PSMA PET/CT images: deep learning method vs. conventional PET/CT processing.
Nuclear medicine communications
Sep 3, 2024
PURPOSE: This study demonstrates the feasibility and benefits of using a deep learning-based approach for attenuation correction in [ 68 Ga]Ga-PSMA PET scans.
The impact of multicentric datasets for the automated tumor delineation in primary prostate cancer using convolutional neural networks on F-PSMA-1007 PET.
Radiation oncology (London, England)
Aug 7, 2024
PURPOSE: Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of radiation oncology, significantly advancing the precision of contouring practices. However, the adaptability of these algorithms across diverse scanner...
Machine learning-based analysis of Ga-PSMA-11 PET/CT images for estimation of prostate tumor grade.
Physical and engineering sciences in medicine
Mar 25, 2024
Early diagnosis of prostate cancer, the most common malignancy in men, can improve patient outcomes. Since the tissue sampling procedures are invasive and sometimes inconclusive, an alternative image-based method can prevent possible complications an...
Deep Learning Empowers the Discovery of Self-Assembling Peptides with Over 10 Trillion Sequences.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Sep 25, 2023
Self-assembling of peptides is essential for a variety of biological and medical applications. However, it is challenging to investigate the self-assembling properties of peptides within the complete sequence space due to the enormous sequence quanti...
Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides.
Journal of chemical theory and computation
Feb 18, 2022
The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has b...
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