AIMC Topic: Deep Learning

Clear Filters Showing 20321 to 20330 of 28423 articles

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.

Laboratory investigation; a journal of technical methods and pathology Aug 10, 2020
As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)popula...
Endocrine Disruptors Receptors, Estrogen Protein Binding Mice Models, Statistical Databases, Chemical Computational Biology Animals Deep Learning Machine Learning Algorithms Humans
View on PubMed DOI

Deep learning and level set approach for liver and tumor segmentation from CT scans.

Journal of applied clinical medical physics Aug 10, 2020
PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important task for hepatic surgical planning. Manual segmentation of liver and tumors is tedious, time-consuming, and biased to the clinician experience. Theref...
Tomography, X-Ray Computed Humans Deep Learning Neural Networks, Computer Liver Neoplasms Image Processing, Computer-Assisted
View on PubMed DOI

MRI-Based Deep-Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma.

Journal of magnetic resonance imaging : JMRI Aug 9, 2020
BACKGROUND: Distant metastasis is the primary cause of treatment failure in locoregionally advanced nasopharyngeal carcinoma (LANPC).
Humans Retrospective Studies Deep Learning Magnetic Resonance Imaging Chemoradiotherapy Nasopharyngeal Carcinoma Epstein-Barr Virus Infections Herpesvirus 4, Human Nasopharyngeal Neoplasms
View on PubMed DOI

DeepPred-SubMito: A Novel Submitochondrial Localization Predictor Based on Multi-Channel Convolutional Neural Network and Dataset Balancing Treatment.

International journal of molecular sciences Aug 9, 2020
Mitochondrial proteins are physiologically active in different compartments, and their abnormal location will trigger the pathogenesis of human mitochondrial pathologies. Correctly identifying submitochondrial locations can provide information for di...
Algorithms Deep Learning Mitochondria Protein Transport Computational Biology Humans Mitochondrial Proteins Neural Networks, Computer Mitochondrial Membranes
View on PubMed DOI

Rule-based automatic diagnosis of thyroid nodules from intraoperative frozen sections using deep learning.

Artificial intelligence in medicine Aug 9, 2020
Frozen sections provide a basis for rapid intraoperative diagnosis that can guide surgery, but the diagnoses often challenge pathologists. Here we propose a rule-based system to differentiate thyroid nodules from intraoperative frozen sections using ...
Frozen Sections Thyroid Nodule Probability Neural Networks, Computer Deep Learning Humans
View on PubMed DOI

Development of a Deep Learning-Based Model for Diagnosing Breast Nodules With Ultrasound.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Aug 8, 2020
OBJECTIVES: Artificial intelligence (AI) has been an important addition to medicine. We aimed to explore the use of deep learning (DL) to distinguish benign from malignant lesions with breast ultrasound (BUS).
Deep Learning Ultrasonography ROC Curve Female Humans Sensitivity and Specificity Artificial Intelligence
View on PubMed DOI

Development and validation of two artificial intelligence models for diagnosing benign, pigmented facial skin lesions.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) Aug 8, 2020
OBJECTIVE: This study used deep learning for diagnosing common, benign hyperpigmentation.
Deep Learning Skin Skin Diseases Neural Networks, Computer Artificial Intelligence Humans
View on PubMed DOI

Technical Note: Deep Learning approach for automatic detection and identification of patient positioning devices for radiation therapy.

Medical physics Aug 8, 2020
PURPOSE: Automatic detection and identification of setup devices, using a deep convolutional neural network (CNN) for real-time multiclass object detection, has the potential to reduce errors in the treatment delivery process by avoiding documentatio...
Deep Learning Automation Patient Positioning Humans Neural Networks, Computer
View on PubMed DOI

Fusion of multiple segmentations of medical images using OVASSION and Deep Learning methods: Application to CT-Scans for tumoral kidney.

Computers in biology and medicine Aug 8, 2020
Nephroblastoma is the most common kidney tumour in children. Its diagnosis is based on imagery. In the SAIAD project, we have designed a platform for optimizing the segmentation of deformed kidney and tumour with a small dataset, using Artificial Int...
Humans Deep Learning Child Image Processing, Computer-Assisted Artificial Intelligence Tomography, X-Ray Computed Kidney Kidney Neoplasms
View on PubMed DOI

Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish.

Sensors (Basel, Switzerland) Aug 8, 2020
Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment ...
Fishes Animals Respiration Deep Learning Ammonia Behavior, Animal Aquaculture
View on PubMed DOI
Popular Topics
Recent Journals