AIMC Topic: Deep Learning

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Raman spectroscopy combined with deep learning for rapid detection of melanoma at the single cell level.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Melanoma is an aggressive and metastatic skin cancer caused by genetic mutations in melanocytes, and its incidence is increasing year by year. Understanding the gene mutation information of melanoma cases is very important for its precise treatment. ...

Brain Age Prediction/Classification through Recurrent Deep Learning with Electroencephalogram Recordings of Seizure Subjects.

Sensors (Basel, Switzerland)
With modern population growth and an increase in the average lifespan, more patients are becoming afflicted with neurodegenerative diseases such as dementia and Alzheimer's. Patients with a history of epilepsy, drug abuse, and mental health disorders...

DEEP LEARNING ALGORITHMS HAVE HIGH ACCURACY FOR AUTOMATED LANDMARK DETECTION ON 2D LATERAL CEPHALOGRAMS.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Deep learning for cephalometric landmark detection: systematic review and meta-analysis. Schwendicke F, Chaurasia A, Arsiwala L, Lee JH, Elhennawy K, Jost-Brinkmann PG, Demarco F, Krois J. Clin Oral Invest...

Deep Learning-Based NMPC for Local Motion Planning of Last-Mile Delivery Robot.

Sensors (Basel, Switzerland)
Feasible local motion planning for autonomous mobile robots in dynamic environments requires predicting how the scene evolves. Conventional navigation stakes rely on a local map to represent how a dynamic scene changes over time. However, these navig...

Determining the Stir-Frying Degree of Praeparatus Based on Deep Learning and Transfer Learning.

Sensors (Basel, Switzerland)
Gardeniae Fructus (GF) is one of the most widely used traditional Chinese medicines (TCMs). Its processed product, Praeparatus (GFP), is often used as medicine; hence, there is an urgent need to determine the stir-frying degree of GFP. In this paper...

Segmentation for Multi-Rock Types on Digital Outcrop Photographs Using Deep Learning Techniques.

Sensors (Basel, Switzerland)
The basic identification and classification of sedimentary rocks into sandstone and mudstone are important in the study of sedimentology and they are executed by a sedimentologist. However, such manual activity involves countless hours of observation...

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction.

Scientific reports
The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is de...

Kidney Tumor Detection and Classification Based on Deep Learning Approaches: A New Dataset in CT Scans.

Journal of healthcare engineering
Kidney tumor (KT) is one of the diseases that have affected our society and is the seventh most common tumor in both men and women worldwide. The early detection of KT has significant benefits in reducing death rates, producing preventive measures th...

Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated radiation therapy. However, delineation is time-consuming and susceptible to interobserver variability (IOV). Based on a manual contouring process co...

Deep-learning-reconstructed high-resolution 3D cervical spine MRI for foraminal stenosis evaluation.

Skeletal radiology
OBJECTIVE: To compare standard-of-care two-dimensional MRI acquisitions of the cervical spine with those from a single three-dimensional MRI acquisition, reconstructed using a deep-learning-based reconstruction algorithm. We hypothesized that the imp...