AIMC Topic: Deep Learning

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Deep-Learning-Based Mixture Identification for Nuclear Magnetic Resonance Spectroscopy Applied to Plant Flavors.

Molecules (Basel, Switzerland)
Nuclear magnetic resonance (NMR) is a crucial technique for analyzing mixtures consisting of small molecules, providing non-destructive, fast, reproducible, and unbiased benefits. However, it is challenging to perform mixture identification because o...

Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models.

International journal of molecular sciences
The data explosion driven by advancements in genomic research, such as high-throughput sequencing techniques, is constantly challenging conventional methods used in genomics. In parallel with the urgent demand for robust algorithms, deep learning has...

Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis.

Biomedical engineering online
PURPOSE: The contouring of organs at risk (OARs) in head and neck cancer radiation treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies have applied deep learning (DL) algorithms to automatically contour head and...

Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions.

BMC bioinformatics
BACKGROUND: During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural lang...

Deep learning based identification of pituitary adenoma on surgical endoscopic images: a pilot study.

Neurosurgical review
Accurate tumor identification during surgical excision is necessary for neurosurgeons to determine the extent of resection without damaging the surrounding tissues. No conventional technologies have achieved reliable performance for pituitary adenoma...

Performance of CT-based deep learning in diagnostic assessment of suspicious lateral lymph nodes in papillary thyroid cancer: a prospective diagnostic study.

International journal of surgery (London, England)
BACKGROUND: Preoperative evaluation of the metastasis status of lateral lymph nodes (LNs) in papillary thyroid cancer is challenging. Strategies for using deep learning to diagnosis of lateral LN metastasis require additional development and testing....

Identification and validation of a pyroptosis-related signature in identifying active tuberculosis via a deep learning algorithm.

Frontiers in cellular and infection microbiology
INTRODUCTION: Active tuberculosis (ATB), instigated by Mycobacterium tuberculosis (M.tb), rises as a primary instigator of morbidity and mortality within the realm of infectious illnesses. A significant portion of M.tb infections maintain an asymptom...

Early pigment spot segmentation and classification from iris cellular image analysis with explainable deep learning and multiclass support vector machine.

Biochemistry and cell biology = Biochimie et biologie cellulaire
Globally, retinal disorders impact thousands of individuals. Early diagnosis and treatment of these anomalies might halt their development and prevent many people from developing preventable blindness. Iris spot segmentation is critical due to acquir...

Automated quantification of vacuole fusion and lipophagy in from fluorescence and cryo-soft X-ray microscopy data using deep learning.

Autophagy
During starvation in the yeast vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and...