AIMC Topic: Deep Learning

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Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico May 1, 2025
OBJECTIVE: The objective of this study was to analyze the incidence and overall survival (OS) of osteosarcoma (OSC) and Ewing's sarcoma (EWS) in a pediatric and adolescent population, employing machine learning (ML) and deep learning (DL) models to p...
Neoplasm Metastasis Sarcoma, Ewing Child, Preschool Child Nomograms Osteosarcoma Bone Neoplasms Infant Deep Learning Adolescent Incidence Humans Machine Learning Prognosis Female Infant, Newborn Young Adult Survival Rate Male
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Predicting postoperative prognosis in clear cell renal cell carcinoma using a multiphase CT-based deep learning model.

Abdominal radiology (New York) May 1, 2025
BACKGROUND: Some clinicopathological risk stratification systems (CRSSs) such as the leibovich score have been used to predict the postoperative prognosis of patients with clear cell renal cell carcinoma (ccRCC), but there are no reliable noninvasive...
Kidney Predictive Value of Tests Kidney Neoplasms Carcinoma, Renal Cell Adult Male Middle Aged Deep Learning Humans Prognosis Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over
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Deep Learning-Based Classification of Early-Stage Mycosis Fungoides and Benign Inflammatory Dermatoses on H&E-Stained Whole-Slide Images: A Retrospective, Proof-of-Concept Study.

The Journal of investigative dermatology May 1, 2025
The diagnosis of early-stage mycosis fungoides (MF) is challenging owing to shared clinical and histopathological features with benign inflammatory dermatoses. Recent evidence has shown that deep learning (DL) can assist pathologists in cancer classi...
Humans Adult Male Middle Aged Deep Learning Diagnosis, Differential Retrospective Studies Female Skin Neoplasms Aged Proof of Concept Study Neoplasm Staging Biopsy Dermatitis Skin Mycosis Fungoides
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Feasibility of deep learning algorithm in diagnosing lumbar central canal stenosis using abdominal CT.

Skeletal radiology May 1, 2025
OBJECTIVE: To develop a deep learning algorithm for diagnosing lumbar central canal stenosis (LCCS) using abdominal CT (ACT) and lumbar spine CT (LCT).
Lumbar Vertebrae Feasibility Studies Spinal Stenosis Radiography, Abdominal Tomography, X-Ray Computed Female Aged Aged, 80 and over Sensitivity and Specificity Male Middle Aged Deep Learning Humans Radiographic Image Interpretation, Computer-Assisted Algorithms Retrospective Studies
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Multimodal sentiment analysis leveraging the strength of deep neural networks enhanced by the XGBoost classifier.

Computer methods in biomechanics and biomedical engineering May 1, 2025
Multimodal sentiment analysis, an increasingly vital task in the realms of natural language processing and machine learning, addresses the nuanced understanding of emotions and sentiments expressed across diverse data sources. This study presents the...
Natural Language Processing Boosting Machine Learning Algorithms Humans Neural Networks, Computer Deep Learning Emotions
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Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study.

Angiology May 1, 2025
To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neur...
Female Cardiac-Gated Imaging Techniques Humans Reproducibility of Results Middle Aged Aged Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Male Deep Learning Retrospective Studies Coronary Artery Disease Tomography, X-Ray Computed Vascular Calcification Electrocardiography Computed Tomography Angiography Predictive Value of Tests Coronary Angiography
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Prediction of Hypoglycemia From Continuous Glucose Monitoring in Insulin-Treated Patients With Type 2 Diabetes Using Transfer Learning on Type 1 Diabetes Data: A Deep Transfer Learning Approach.

Journal of diabetes science and technology May 1, 2025
BACKGROUND: Hypoglycemia is common in insulin-treated type 2 diabetes (T2D) patients, which can lead to decreased quality of life or premature death. Deep learning models offer promise of accurate predictions, but data scarcity poses a challenge. Thi...
Humans Continuous Glucose Monitoring Middle Aged Diabetes Mellitus, Type 1 Deep Learning Neural Networks, Computer Hypoglycemic Agents Blood Glucose Female Hypoglycemia Insulin Adult Blood Glucose Self-Monitoring Diabetes Mellitus, Type 2 Male
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Artificial intelligence in the detection and classification of dental caries.

The Journal of prosthetic dentistry May 1, 2025
STATEMENT OF PROBLEM: Automated detection of dental caries could enhance early detection, save clinician time, and enrich treatment decisions. However, a reliable system is lacking.
Deep Learning Image Processing, Computer-Assisted Dental Caries Radiography, Bitewing Humans Artificial Intelligence Algorithms
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Automatic GRBAS Scoring of Pathological Voices using Deep Learning and a Small Set of Labeled Voice Data.

Journal of voice : official journal of the Voice Foundation May 1, 2025
OBJECTIVES: Auditory-perceptual evaluation frameworks, such as the grade-roughness-breathiness-asthenia-strain (GRBAS) scale, are the gold standard for the quantitative evaluation of pathological voice quality. However, the evaluation is subjective; ...
Voice Quality Predictive Value of Tests Adult Automation Signal Processing, Computer-Assisted Humans Male Acoustics Judgment Neural Networks, Computer Severity of Illness Index Observer Variation Female Speech Acoustics Deep Learning Reproducibility of Results Voice Disorders Time Factors Speech Production Measurement
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Determinants of ascending aortic morphology: cross-sectional deep learning-based analysis on 25 073 non-contrast-enhanced NAKO MRI studies.

European heart journal. Cardiovascular Imaging Apr 30, 2025
AIMS: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resona...
Humans Female Aged Adult Cross-Sectional Studies Age Factors Male Sex Factors Middle Aged Germany Deep Learning Aorta, Thoracic Cohort Studies Magnetic Resonance Angiography Imaging, Three-Dimensional
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