AIMC Topic: Deep Learning

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Development and validation of an automatic classification algorithm for the diagnosis of Alzheimer's disease using a high-performance interpretable deep learning network.

European radiology
OBJECTIVES: To develop and validate an automatic classification algorithm for diagnosing Alzheimer's disease (AD) or mild cognitive impairment (MCI).

Deep learning on independent spatial EEG activity patterns delineates time windows relevant for response inhibition.

Psychophysiology
Inhibitory control processes are an important aspect of executive functions and goal-directed behavior. However, the mostly correlative nature of neurophysiological studies was not able to provide insights which aspects of neural dynamics can best pr...

Deep learning-based classification of organs at risk and delineation guideline in pelvic cancer radiation therapy.

Journal of applied clinical medical physics
Deep learning (DL) models for radiation therapy (RT) image segmentation require accurately annotated training data. Multiple organ delineation guidelines exist; however, information on the used guideline is not provided with the delineation. Extracti...

Diagnosis of Developmental Dysplasia of the Hip by Ultrasound Imaging Using Deep Learning.

Journal of pediatric orthopedics
BACKGROUND: A timely diagnosis of developmental dysplasia of the hip (DDH) is important for satisfactory clinical outcomes. Ultrasonography is a useful tool for DDH screening; however, it is technically demanding. We hypothesized that deep learning c...

Efficient Deep Learning Based Hybrid Model to Detect Obstructive Sleep Apnea.

Sensors (Basel, Switzerland)
An increasing number of patients and a lack of awareness about obstructive sleep apnea is a point of concern for the healthcare industry. Polysomnography is recommended by health experts to detect obstructive sleep apnea. The patient is paired up wit...

Improving variant calling using population data and deep learning.

BMC bioinformatics
Large-scale population variant data is often used to filter and aid interpretation of variant calls in a single sample. These approaches do not incorporate population information directly into the process of variant calling, and are often limited to ...

Deep learning-based protoacoustic signal denoising for proton range verification.

Biomedical physics & engineering express
Proton therapy is a type of radiation therapy that can provide better dose distribution compared to photon therapy by delivering most of the energy at the end of range, which is called the Bragg peak (BP). The protoacoustic technique was developed to...

Classification of normal and abnormal fetal heart ultrasound images and identification of ventricular septal defects based on deep learning.

Journal of perinatal medicine
OBJECTIVES: Congenital heart defects (CHDs) are the most common birth defects. Recently, artificial intelligence (AI) was used to assist in CHD diagnosis. No comparison has been made among the various types of algorithms that can assist in the prenat...

Precise Brain-shift Prediction by New Combination of W-Net Deep Learning for Neurosurgical Navigation.

Neurologia medico-chirurgica
Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurgeries. We generated updated magnetic resonance images (uMR) in this study to compensate for brain shifts after dural opening using a convolutional neu...

Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.

Cancer medicine
BACKGROUND: The study aims to evaluate the performance of three advanced machine learning algorithms and a traditional Cox proportional hazard (CoxPH) model in predicting the overall survival (OS) of patients with pancreatic neuroendocrine neoplasms ...