AIMC Topic: Deep Learning

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Deep learning-enabled filter-free fluorescence microscope.

Science advances
Optical filtering is an indispensable part of fluorescence microscopy for selectively highlighting molecules labeled with a specific fluorophore and suppressing background noise. However, the utilization of optical filtering sets increases the comple...

Artificial intelligence-based multi-modal multi-tasks analysis reveals tumor molecular heterogeneity, predicts preoperative lymph node metastasis and prognosis in papillary thyroid carcinoma: a retrospective study.

International journal of surgery (London, England)
BACKGROUND: Papillary thyroid carcinoma (PTC) is the predominant form of thyroid cancer globally, especially when lymph node metastasis (LNM) occurs. Molecular heterogeneity, driven by genetic alterations and tumor microenvironment components, contri...

Generalizability, robustness, and correction bias of segmentations of thoracic organs at risk in CT images.

European radiology
OBJECTIVE: This study aims to assess and compare two state-of-the-art deep learning approaches for segmenting four thoracic organs at riskĀ (OAR)-the esophagus, trachea, heart, and aorta-in CT images in the context of radiotherapy planning.

Interpretable deep learning for acoustic leak detection in water distribution systems.

Water research
Leak detection is crucial for ensuring the safety of water systems and conserving water resources. However, current research on machine learning methods for leak detection focuses excessively on model development while neglecting model interpretabili...

WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.

Magnetic resonance in medicine
PURPOSE: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal fro...

Knee osteoarthritis severity detection using deep inception transfer learning.

Computers in biology and medicine
Osteoarthritis (OA) is a prevalent condition resulting in physical limitations. Early detection of OA is critical to effectively manage this condition. However, the diagnosis of early-stage arthritis remains challenging. The Kellgren and Lawrence (KL...

Deep Learning-Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell...

NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

Journal of proteome research
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on im...

Human intention recognition for trauma resuscitation: An interpretable deep learning approach for medical process data.

Journal of biomedical informatics
OBJECTIVE: Trauma resuscitation is the initial evaluation and management of injured patients in the emergency department. This time-critical process requires the simultaneous pursuit of multiple resuscitation goals. Recognizing whether the required g...