AIMC Topic: Predictive Value of Tests
Clear Filters Showing 2011 to 2020 of 2216 articles
Machine Learning-based Prediction Model for Treatment of Acromegaly With First-generation Somatostatin Receptor Ligands.
The Journal of clinical endocrinology and metabolism
Jun 16, 2021
CONTEXT: Artificial intelligence (AI), in particular machine learning (ML), may be used to deeply analyze biomarkers of response to first-generation somatostatin receptor ligands (fg-SRLs) in the treatment of acromegaly.
Prediction of Adult Height by Machine Learning Technique.
The Journal of clinical endocrinology and metabolism
Jun 16, 2021
CONTEXT: Prediction of AH is frequently undertaken in the clinical setting. The commonly used methods are based on the assessment of skeletal maturation. Predictive algorithms generated by machine learning, which can already automatically drive cars ...
Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study.
The Lancet. Digital health
Jun 1, 2021
BACKGROUND: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heteroge...
Predictive Value of Tests
Area Under Curve
Radiography
Progression-Free Survival
Disease-Free Survival
Middle Aged
Deep Learning
China
ROC Curve
Proportional Hazards Models
Stomach
Chemotherapy, Adjuvant
Humans
Neural Networks, Computer
Prognosis
Retrospective Studies
Tomography, X-Ray Computed
Female
Stomach Neoplasms
Biomarkers, Tumor
Male
A Deep-Learning Diagnostic Support System for the Detection of COVID-19 Using Chest Radiographs: A Multireader Validation Study.
Investigative radiology
Jun 1, 2021
MATERIALS AND METHODS: Five publicly available databases comprising normal CXR, confirmed COVID-19 pneumonia cases, and other pneumonias were used. After the harmonization of the data, the training set included 7966 normal cases, 5451 with other pneu...
Rib fracture detection in computed tomography images using deep convolutional neural networks.
Medicine
May 21, 2021
To evaluate the rib fracture detection performance in computed tomography (CT) images using a software based on a deep convolutional neural network (DCNN) and compare it with the rib fracture diagnostic performance of doctors.We included CT images fr...
AntiCP 2.0: an updated model for predicting anticancer peptides.
Briefings in bioinformatics
May 20, 2021
Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides...
Predicting microRNA-disease associations from lncRNA-microRNA interactions via Multiview Multitask Learning.
Briefings in bioinformatics
May 20, 2021
MOTIVATION: Identifying microRNAs that are associated with different diseases as biomarkers is a problem of great medical significance. Existing computational methods for uncovering such microRNA-diseases associations (MDAs) are mostly developed unde...
Deep learning for prediction of fractional flow reserve from resting coronary pressure curves.
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
May 17, 2021
BACKGROUND: It would be ideal for a non-hyperaemic index to predict fractional flow reserve (FFR) more accurately, given FFR's extensive validation in a multitude of clinical settings.
Using Predictive Modeling and Machine Learning to Identify Patients Appropriate for Outpatient Anterior Cervical Fusion and Discectomy.
Spine
May 15, 2021
STUDY DESIGN: Retrospective, case-control.
Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs.
The Lancet. Digital health
May 1, 2021
BACKGROUND: Coronary artery calcium (CAC) score is a clinically validated marker of cardiovascular disease risk. We developed and validated a novel cardiovascular risk stratification system based on deep-learning-predicted CAC from retinal photograph...
Male
Republic of Korea
Retina
Cardiovascular Diseases
Humans
United Kingdom
ROC Curve
Middle Aged
Female
Algorithms
Predictive Value of Tests
Proportional Hazards Models
Risk Assessment
Aged
Area Under Curve
Kaplan-Meier Estimate
Deep Learning
Adult
Singapore
Vascular Calcification
Coronary Artery Disease
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