AIMC Topic: Middle Aged

Clear Filters Showing 16371 to 16380 of 17155 articles

Optimization of treatment strategy by using a machine learning model to predict survival time of patients with malignant glioma after radiotherapy.

Journal of radiation research Nov 22, 2019
The purpose of this study was to predict the survival time of patients with malignant glioma after radiotherapy with high accuracy by considering additional clinical factors and optimize the prescription dose and treatment duration for individual pat...
Child Models, Theoretical Glioma Support Vector Machine Survival Analysis Adult Male Middle Aged Adolescent Time Factors Dose-Response Relationship, Radiation Humans Machine Learning Female Aged Aged, 80 and over Young Adult
View on PubMed DOI

Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer.

World journal of gastroenterology Nov 21, 2019
BACKGROUND: Because of the powerful abilities of self-learning and handling complex biological information, artificial neural network (ANN) models have been widely applied to disease diagnosis, imaging analysis, and prognosis prediction. However, the...
Young Adult Adult Stomach Neoplasms Male Middle Aged China Adolescent Child Logistic Models Precision Medicine Prognosis Female Aged Humans Aged, 80 and over Neural Networks, Computer Biomarkers
View on PubMed DOI

Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Nov 15, 2019
STUDY OBJECTIVES: Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and incre...
Humans Adult Surveys and Questionnaires Self Care Machine Learning Sleep Apnea, Obstructive Sensitivity and Specificity Decision Support Techniques Calibration Male Retrospective Studies Polysomnography Middle Aged Female Aged
View on PubMed DOI

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography.

European heart journal Nov 14, 2019
BACKGROUND: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). Howeve...
Genetic Markers Plaque, Atherosclerotic Computed Tomography Angiography Aged Male Middle Aged Risk Assessment Humans Gene Expression Profiling Transcriptome Machine Learning Algorithms Case-Control Studies Phenotype Follow-Up Studies Female Adipose Tissue Coronary Artery Disease
View on PubMed DOI

Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

Metabolic syndrome and related disorders Nov 1, 2019
We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibr...
Hypertension Metabolic Syndrome Decision Making Non-alcoholic Fatty Liver Disease Disease Progression Prevalence Humans Severity of Illness Index Diabetes Mellitus, Type 2 Retrospective Studies Liver Cirrhosis Female Adult Aged Sensitivity and Specificity Machine Learning Cross-Sectional Studies Algorithms Male Prognosis Middle Aged
View on PubMed DOI

Development and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome.

Obstetrics and gynecology Nov 1, 2019
OBJECTIVE: To develop and externally validate a prediction model for anticholinergic response in patients with overactive bladder (OAB).
Female Reproducibility of Results Aged Adult Middle Aged Humans Machine Learning Algorithms Prognosis Predictive Value of Tests Area Under Curve Urinary Bladder, Overactive Urinary Incontinence Cholinergic Antagonists
View on PubMed DOI

Application of Artificial Intelligence-based Image Optimization for Computed Tomography Angiography of the Aorta With Low Tube Voltage and Reduced Contrast Medium Volume.

Journal of thoracic imaging Nov 1, 2019
PURPOSE: The purpose of this study was to evaluate the impact of artificial intelligence (AI)-based noise reduction algorithm on aorta computed tomography angiography (CTA) image quality (IQ) at 80 kVp tube voltage and 40 mL contrast medium (CM).
Prospective Studies Female Aged Aged, 80 and over Adult Humans Artificial Intelligence Aorta, Thoracic Image Enhancement Signal-To-Noise Ratio Triiodobenzoic Acids Computed Tomography Angiography Aortic Diseases Male Middle Aged Adolescent Contrast Media Radiographic Image Interpretation, Computer-Assisted
View on PubMed DOI

Interaction Effects of Gene Polymorphisms and Obesity on Nonalcoholic Fatty Liver Disease.

Biomedical and environmental sciences : BES Oct 1, 2019
Polymorphism, Genetic Middle Aged Humans Multifactor Dimensionality Reduction China Female Aged Models, Theoretical Aged, 80 and over Obesity Male Non-alcoholic Fatty Liver Disease
View on PubMed DOI

Histogram analysis of absolute cerebral blood volume map can distinguish glioblastoma from solitary brain metastasis.

Medicine Oct 1, 2019
Glioblastoma multiforme (GBM) is difficult to be separated from solitary brain metastasis (sBM) in clinical practice. This study aimed to distinguish two entities by the histogram analysis of absolute cerebral blood volume (CBV) map.From March 2016 t...
Cerebral Blood Volume Humans Machine Learning Retrospective Studies ROC Curve Female Diagnosis, Differential Aged Predictive Value of Tests Brain Neoplasms Glioblastoma Male Image Interpretation, Computer-Assisted Middle Aged
View on PubMed DOI

Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.

JCO clinical cancer informatics Oct 1, 2019
PURPOSE: Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand can...
Medical Informatics Humans Algorithms California Decision Support Systems, Clinical Databases, Factual Female Follow-Up Studies Aged Natural Language Processing Adult Registries Breast Neoplasms Neoplasm Recurrence, Local Middle Aged Time Factors
View on PubMed DOI
Popular Topics
Recent Journals