AIMC Topic: Deep Learning

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Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle.

PloS one
In this study, we present a deep learning model for fracture classification on shoulder radiographs using a convolutional neural network (CNN). The primary aim was to evaluate the classification performance of the CNN for proximal humeral fractures (...

Deep Learning Based Walking Tasks Classification in Older Adults Using fNIRS.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Decline in gait features is common in older adults and an indicator of increased risk of disability, morbidity, and mortality. Under dual task walking (DTW) conditions, further degradation in the performance of both the gait and the secondary cogniti...

Diabetic Retinopathy Screening Using Smartphone-Based Fundus Photography and Deep-Learning Artificial Intelligence in the Yucatan Peninsula: A Field Study.

Journal of diabetes science and technology
BACKGROUND: To compare the performance of Medios (offline) and EyeArt (online) artificial intelligence (AI) algorithms for detecting diabetic retinopathy (DR) on images captured using fundus-on-smartphone photography in a remote outreach field settin...

Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning.

Annals of biomedical engineering
The large amount of training samples required to develop a deep learning brain injury model demands enormous computational resources. Here, we study how a transformer neural network (TNN) of high accuracy can be used to efficiently generate pretraini...

AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.

Journal of neuroradiology = Journal de neuroradiologie
PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-based three-class classification of glioblastoma (GBM), intracranial metastatic disease (IMD) and primary CNS lymphoma (PCNSL).

A Novel Deep Learning Algorithm for Human Papillomavirus Infection Prediction in Head and Neck Cancers Using Routine Histology Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The etiology of head and neck squamous cell carcinoma (HNSCC) involves multiple carcinogens, such as alcohol, tobacco, and infection with human papillomavirus (HPV). Because HPV infection influences the prognosis, treatment, and survival of patients ...

Deep-learning predicted PET can be subtracted from the true clinical fluorodeoxyglucose PET co-registered to MRI to identify the epileptogenic zone in focal epilepsy.

Epilepsia open
OBJECTIVE: Normal interictal [ F]FDG-PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co-registered to MRI) can then be used to compare epilepsy pa...

Cycle-level traffic conflict prediction at signalized intersections with LiDAR data and Bayesian deep learning.

Accident; analysis and prevention
Real-time safety prediction models are vital in proactive road safety management strategies. This study develops models to predict traffic conflicts at signalized intersections at the signal cycle level, using advanced Bayesian deep learning techniqu...

Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT.

Journal of cancer research and clinical oncology
PURPOSE: To investigate the performance of deep learning and radiomics features of intra-tumoral region (ITR) and peri-tumoral region (PTR) in the diagnosing of breast cancer lung metastasis (BCLM) and primary lung cancer (PLC) with low-dose CT (LDCT...

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection.

Clinical and molecular hepatology
BACKGROUND/AIMS: The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorith...