AIMC Topic: Deep Learning

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Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach.

Scientific reports
Chest X-rays are the most economically viable diagnostic imaging test for active pulmonary tuberculosis screening despite the high sensitivity and low specificity when interpreted by clinicians or radiologists. Computer aided detection (CAD) algorith...

Localization and quantification of glottal gaps on deep learning segmentation of vocal folds.

Scientific reports
The entire glottis has mostly been the focus in the tracking of the vocal folds, both manually and automatically. From a treatment point of view, the various regions of the glottis are of specific interest. The aim of the study was to test if it was ...

Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Deep-learning-based computer-aided diagnosis (DL-CAD) systems using MRI for prostate cancer (PCa) detection have demonstrated good performance. Nevertheless, DL-CAD systems are vulnerable to high heterogeneities in DWI, which can interfer...

Predicting prime editing efficiency and product purity by deep learning.

Nature biotechnology
Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here we conducted a high-throughput screen to analyze prime editing outcomes of 92,423...

Deep learning for detecting macroplastic litter in water bodies: A review.

Water research
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems. Accurate detection of macroplastic litter (plastic items >5 mm) in water is essential to estimate t...

Deep learning-based accurate delineation of primary gross tumor volume of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: A large-scale and multi-center study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The problem of obtaining accurate primary gross tumor volume (GTVp) segmentation for nasopharyngeal carcinoma (NPC) on heterogeneous magnetic resonance imaging (MRI) images with deep learning remains unsolved. Herein, we repor...

Assessment of the effects of the biotic and abiotic harmful factors on the amount of industrial wood production with deep learning.

Environmental science and pollution research international
The protection and sustainability of forest assets is possible with planned production of forest products to lead to minimum loss. One of the products obtained from forests is the industrial wood, which is the most important raw material for many sec...

Deep Learning-Based Adaptive Compression and Anomaly Detection for Smart B5G Use Cases Operation.

Sensors (Basel, Switzerland)
The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of netwo...

A deep learning based dual encoder-decoder framework for anatomical structure segmentation in chest X-ray images.

Scientific reports
Automated multi-organ segmentation plays an essential part in the computer-aided diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the anatomical structure segmentation remains challenging due to several indistinct str...

A deep learning based method for automatic analysis of high-throughput droplet digital PCR images.

The Analyst
Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinical diagnosis. ddPCR partitions the reaction solution containing target molecules into a large number ...