AIMC Topic: Deep Learning

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An improved domain-adversarial network for predicting hemodialysis adequacy.

Biomedical physics & engineering express
Hemodialysis (HD) is the primary life-sustaining treatment for patients with end-stage renal disease (ESRD). However, current real-time monitoring methods during dialysis are costly, complex, and not widely adopted. Therefore, this study aims to prop...

Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Identification of the neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural circuits. Yet, modern recording probes have limited power to resolve neuron identity. Here, we pr...

Mangrove species classification using a proposed ensemble U-Net model and Planet satellite imagery: A case study in Ngoc Hien district, Ca Mau province, Vietnam.

PloS one
Land cover and plant species identification using satellite images and deep learning approaches have recently been a widely addressed area of research. However, mangroves, a specific species that have significantly declined in quantity and quality wo...

MSMCE: A novel representation module for classification of raw mass spectrometry data.

PloS one
Mass spectrometry (MS) analysis plays a crucial role in the biomedical field; however, the high dimensionality and complexity of MS data pose significant challenges for feature extraction and classification. Deep learning has become a dominant approa...

Integrating Deep Learning and Real-Time Imaging to Visualize In Situ Self-Assembly of Self-Healing Interpenetrating Polymer Networks Formed by Protein and Polysaccharide Fibers.

ACS applied materials & interfaces
Fibrillar protein hydrogels are promising sustainable biomaterials for biomedical applications, but their practical use is often limited by insufficient mechanical strength and stability. To address these challenges, we transformed native proteins in...

A novel approach to smart-assisted schizophrenia screening based on Raman spectroscopy and deep learning.

Scientific reports
In this study, serum Raman spectra are introduced into the screening of schizophrenia. We collect serum Raman spectra from schizophrenic and healthy individuals, classified them based on four convolutional neural networks, and developed an assisted s...

The First Seasonal Green View Index Mapping Dataset across Chinese cities powered by deep learning.

Scientific data
Multi-temporal mapping of the Green View Index (GVI) is crucial for understanding how urban residents perceive seasonal changes in streetscape greenness. Compared to street view imagery (SVI), remote sensing data offers higher temporal frequency and ...

Interactive 3D segmentation for primary gross tumor volume in oropharyngeal cancer.

Scientific reports
Radiotherapy is the main treatment modality of oropharyngeal cancer (OPC), in which an accurate segmentation of primary gross tumor volume (GTVt) is essential but also challenging due to significant interobserver variability and the time consumed in ...

YOLO-LeafNet: a robust deep learning framework for multispecies plant disease detection with data augmentation.

Scientific reports
Plant diseases significantly harm crops, resulting in significant economic losses across the globe. In order to reduce the harm that these diseases produce, plant diseases must be diagnosed accurately and timely manner. In this work, a YOLO-LeafNet a...

Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images.

Scientific reports
Kidney cancer is a leading cause of cancer-related mortality, with renal cell carcinoma (RCC) being the most prevalent form, accounting for 80-85% of all renal tumors. Traditional diagnosis of kidney cancer requires manual examination and analysis of...