AIMC Topic: Deep Learning
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DiffMC-Gen: A Dual Denoising Diffusion Model for Multi-Conditional Molecular Generation.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Apr 1, 2025
The precise and efficient design of potential drug molecules with diverse physicochemical properties has long been a critical challenge. In recent years, the emergence of various deep learning-based de novo molecular generation algorithms offered new...
Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations.
Medical physics
Apr 1, 2025
BACKGROUND: Computed tomography (CT) scans are a major source of medical radiation exposure worldwide. In countries like China, the frequency of CT scans has grown rapidly, thus making available a large volume of organ dose information. With modern c...
Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.
NeuroImage
Apr 1, 2025
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...
Artificial intelligence applied to epilepsy imaging: Current status and future perspectives.
Revue neurologique
Apr 1, 2025
In recent years, artificial intelligence (AI) has become an increasingly prominent focus of medical research, significantly impacting epileptology as well. Studies on deep learning (DL) and machine learning (ML) - the core of AI - have explored their...
Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 1, 2025
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...
Enhancing cell instance segmentation in scanning electron microscopy images via a deep contour closing operator.
Computers in biology and medicine
Apr 1, 2025
Accurately segmenting and individualizing cells in scanning electron microscopy (SEM) images is a highly promising technique for elucidating tissue architecture in oncology. While current artificial intelligence (AI)-based methods are effective, erro...
Multimodal learning-based speech enhancement and separation, recent innovations, new horizons, challenges and real-world applications.
Computers in biology and medicine
Apr 1, 2025
With the increasing global prevalence of disabling hearing loss, speech enhancement technologies have become crucial for overcoming communication barriers and improving the quality of life for those affected. Multimodal learning has emerged as a powe...
A novel skeletal muscle quantitative method and deep learning-based sarcopenia diagnosis for cervical cancer patients treated with radiotherapy.
Medical physics
Apr 1, 2025
BACKGROUND: Sarcopenia is associated with decreased survival in cervical cancer patients treated with radiotherapy. Cone-beam computed tomography (CBCT) was widely used in image-guided radiotherapy. Sarcopenia is assessed by the skeletal muscle index...
Enhancing synchrotron radiation micro-CT images using deep learning: an application of Noise2Inverse on bone imaging.
Journal of synchrotron radiation
Apr 1, 2025
In bone-imaging research, in situ synchrotron radiation micro-computed tomography (SRµCT) mechanical tests are used to investigate the mechanical properties of bone in relation to its microstructure. Low-dose computed tomography (CT) is used to prese...
Deep Learning-driven Microfluidic-SERS to Characterize the Heterogeneity in Exosomes for Classifying Non-Small Cell Lung Cancer Subtypes.
ACS sensors
Apr 1, 2025
Lung cancer exhibits strong heterogeneity, and its early diagnosis and precise subtyping are of great importance, as they can increase the ability to deliver personalized medicines by tailoring therapy regimens. Tissue biopsy, albeit the gold standar...
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