AIMC Topic: Predictive Value of Tests
Clear Filters Showing 1351 to 1360 of 2212 articles
[Prediction of chemotherapy response in primary osteosarcoma using the machine learning technique on radiomic data].
Bulletin du cancer
Oct 3, 2019
INTRODUCTION: Osteosarcoma is the most common malignant bone tumor before 25 years of age. Response to neoadjuvant chemotherapy determines continuation of treatment and is also a powerful prognostic factor. There are currently no reliable ways to eva...
Female
Infant, Newborn
Young Adult
Sensitivity and Specificity
Male
Humans
Machine Learning
Retrospective Studies
Antineoplastic Combined Chemotherapy Protocols
Treatment Outcome
Neoadjuvant Therapy
Magnetic Resonance Imaging
Osteosarcoma
Infant
Adolescent
Child, Preschool
Child
Chemotherapy, Adjuvant
Bone Neoplasms
Predictive Value of Tests
France
Analysis of Variance
Potential of automatic diagnosis system with linked color imaging for diagnosis of Helicobacter pylori infection.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Oct 2, 2019
BACKGROUND AND AIM: It is necessary to establish universal methods for endoscopic diagnosis of Helicobacter pylori (HP) infection, such as computer-aided diagnosis. In the present study, we propose a multistage diagnosis algorithm for HP infection.
Artificial intelligence using a convolutional neural network for automatic detection of small-bowel angioectasia in capsule endoscopy images.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Oct 2, 2019
BACKGROUND AND AIM: Although small-bowel angioectasia is reported as the most common cause of bleeding in patients and frequently diagnosed by capsule endoscopy (CE) in patients with obscure gastrointestinal bleeding, a computer-aided detection metho...
Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer.
JAMA network open
Oct 2, 2019
IMPORTANCE: Machine learning algorithms could identify patients with cancer who are at risk of short-term mortality. However, it is unclear how different machine learning algorithms compare and whether they could prompt clinicians to have timely conv...
Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity.
Drug and alcohol dependence
Oct 1, 2019
BACKGROUND: This longitudinal study explored the utility of machine learning (ML) methodology in predicting the trajectory of severity of substance use from childhood to thirty years of age using a set of psychological and health characteristics.
Predicting post-stroke pneumonia using deep neural network approaches.
International journal of medical informatics
Oct 1, 2019
BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length of hospital stay and death. Therefore, the timely and accurate prediction of post-stroke pneumonia would be highly valuable in clinical practice. Pre...
Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.
Ophthalmology
Sep 30, 2019
PURPOSE: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SDÂ OCT) optic nerve head images.
A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.
Medical hypotheses
Sep 30, 2019
Magnetic resonance imaging (MRI) images can be used to diagnose brain tumors. Thanks to these images, some methods have so far been proposed in order to distinguish between benign and malignant brain tumors. Many systems attempting to define these tu...
Endocan serum concentration in uninfected newborn infants.
Journal of infection in developing countries
Sep 30, 2019
INTRODUCTION: Endocan is a specific endothelial mediator involved in the inflammatory response. Its role in the diagnosis of sepsis has been studied in adult patients and late onset neonatal sepsis. The clinical signs of early onset sepsis (EOS) are ...
Comparison of CT and MRI images for the prediction of soft-tissue sarcoma grading and lung metastasis via a convolutional neural networks model.
Clinical radiology
Sep 28, 2019
AIM: To realise the automated prediction of soft-tissue sarcoma (STS) grading and lung metastasis based on computed tomography (CT), T1-weighted (T1W) magnetic resonance imaging (MRI), and fat-suppressed T2-weighted MRI (FST2W) via the convolutional ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31875
- Neural Networks, Computer 30159
- Algorithms 27337
- Deep Learning 26831
- Artificial Intelligence 24782
- Robotics 13378
- Image Processing, Computer-Assisted 9711
- Retrospective Studies 9309
- Magnetic Resonance Imaging 6321
- Reproducibility of Results 5666
- Tomography, X-Ray Computed 4857
- Support Vector Machine 4758
- Computational Biology 4319
- Brain 4112
- Computer Simulation 3931
Recent Journals
- Scientific reports 6632
- Sensors (Basel, Switzerland) 4794
- PloS one 4158
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1160
- Journal of chemical information and modeling 1042
- Nature communications 1017
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 870
- Briefings in bioinformatics 853
- Journal of medical Internet research 844