AIMC Topic:
ROC Curve
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Artificial intelligence for detection of periapical lesions on intraoral radiographs: Comparison between convolutional neural networks and human observers.
Oral surgery, oral medicine, oral pathology and oral radiology
Jan 22, 2021
OBJECTIVE: The aim of this study was to compare the diagnostic performance of convolutional neural networks (CNNs) with the performance of human observers for the detection of simulated periapical lesions on periapical radiographs.
Machine Learning Approach for Intraocular Disease Prediction Based on Aqueous Humor Immune Mediator Profiles.
Ophthalmology
Jan 21, 2021
PURPOSE: Various immune mediators have crucial roles in the pathogenesis of intraocular diseases. Machine learning can be used to automatically select and weigh various predictors to develop models maximizing predictive power. However, these techniqu...
Machine Learning
Retinal Detachment
Aqueous Humor
Female
Intraocular Lymphoma
Reproducibility of Results
Retinal Necrosis Syndrome, Acute
Aged
Humans
Inflammation Mediators
Aged, 80 and over
Area Under Curve
Eye Diseases
Adult
Immunoassay
Endophthalmitis
Middle Aged
Cross-Sectional Studies
Flow Cytometry
Diagnosis, Computer-Assisted
Glaucoma, Open-Angle
Male
ROC Curve
Interleukins
Development and validation of a deep-learning-based pediatric early warning system: A single-center study.
Biomedical journal
Jan 18, 2021
BACKGROUND: Early detection and prompt intervention for clinically deteriorating events are needed to improve clinical outcomes. There have been several attempts at this, including the introduction of rapid response teams (RRTs) with early warning sc...
An objective structural and functional reference standard in glaucoma.
Scientific reports
Jan 18, 2021
The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using cle...
QAIS-DSNN: Tumor Area Segmentation of MRI Image with Optimized Quantum Matched-Filter Technique and Deep Spiking Neural Network.
BioMed research international
Jan 18, 2021
Tumor segmentation in brain MRI images is a noted process that can make the tumor easier to diagnose and lead to effective radiotherapy planning. Providing and building intelligent medical systems can be considered as an aid for physicians. In many c...
Development and Internal Validation of Supervised Machine Learning Algorithms for Predicting Clinically Significant Functional Improvement in a Mixed Population of Primary Hip Arthroscopy.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Jan 16, 2021
PURPOSE: To (1) develop and validate a machine learning algorithm to predict clinically significant functional improvements after hip arthroscopy for femoroacetabular impingement syndrome and to (2) develop a digital application capable of providing ...
The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph.
Scientific reports
Jan 15, 2021
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. Th...
Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics.
European radiology
Jan 14, 2021
OBJECTIVE: To investigate the application of machine learning-based ultrasound radiomics in preoperative classification of primary and metastatic liver cancer.
A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning.
Interdisciplinary sciences, computational life sciences
Jan 12, 2021
The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a significant impact on daily life, it also shows its effect in different areas, including public heal...
Schizotypy in Parkinson's disease predicts dopamine-associated psychosis.
Scientific reports
Jan 12, 2021
Psychosis is the most common neuropsychiatric side-effect of dopaminergic therapy in Parkinson's disease (PD). It is still unknown which factors determine individual proneness to psychotic symptoms. Schizotypy is a multifaceted personality trait rela...
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