AIMC Topic: Case-Control Studies

Clear Filters Showing 611 to 620 of 873 articles

Assessing patient risk of central line-associated bacteremia via machine learning.

American journal of infection control Apr 13, 2018
BACKGROUND: Central line-associated bloodstream infections (CLABSIs) contribute to increased morbidity, length of hospital stay, and cost. Despite progress in understanding the risk factors, there remains a need to accurately predict the risk of CLAB...
Child Bacteremia Catheterization, Central Venous Catheter-Related Infections Academic Medical Centers Infant Case-Control Studies Adolescent Child, Preschool Epidemiologic Methods Female Infant, Newborn Aged Aged, 80 and over Young Adult Adult Male Middle Aged Risk Assessment Humans Machine Learning Retrospective Studies
View on PubMed DOI

Feasibility of robot-based perturbed-balance training during treadmill walking in a high-functioning chronic stroke subject: a case-control study.

Journal of neuroengineering and rehabilitation Apr 11, 2018
BACKGROUND: For stroke survivors, balance deficits that persist after the completion of the rehabilitation process lead to a significant risk of falls. We have recently developed a balance-assessment robot (BAR-TM) that enables assessment of balancin...
Middle Aged Case-Control Studies Robotics Postural Balance Walking Humans Biomechanical Phenomena Male Feasibility Studies Survivors Stroke Rehabilitation
View on PubMed DOI

Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.

BMC psychiatry Apr 10, 2018
BACKGROUND: Early diagnosis of schizophrenia could improve the outcome of the illness. Unlike classical between-group comparisons, machine learning can identify subtle disease patterns on a single subject level, which could help realize the potential...
Case-Control Studies Support Vector Machine Schizophrenia Early Diagnosis White Matter Diffusion Tensor Imaging Brain Anisotropy Female Young Adult Adult Humans Male
View on PubMed DOI

Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Gene Expression Profiling Transcriptome Case-Control Studies Adolescent Human Growth Hormone Biomarkers Female Humans Polymorphism, Single Nucleotide Male Machine Learning Growth Disorders Severity of Illness Index Predictive Value of Tests Child, Preschool Principal Component Analysis Child Healthy Volunteers ROC Curve Datasets as Topic Gene Regulatory Networks
View on PubMed DOI

Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia.

PloS one Mar 29, 2018
Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variability of traditional vital signs, such as heart rate and blood pressure, and their inability to detect ...
Wounds and Injuries Hypovolemia Photoplethysmography Humans Blood Volume Support Vector Machine Algorithms Water-Electrolyte Imbalance Female Hemorrhage Adult Male Case-Control Studies
View on PubMed DOI

Urinary Polyamine Biomarker Panels with Machine-Learning Differentiated Colorectal Cancers, Benign Disease, and Healthy Controls.

International journal of molecular sciences Mar 7, 2018
Colorectal cancer (CRC) is one of the most daunting diseases due to its increasing worldwide prevalence, which requires imperative development of minimally or non-invasive screening tests. Urinary polyamines have been reported as potential markers to...
Polyamines Adenomatous Polyposis Coli Case-Control Studies Chromatography, Liquid Diagnosis, Differential Tandem Mass Spectrometry Humans Machine Learning Prognosis Reproducibility of Results Colorectal Neoplasms Biomarkers, Tumor
View on PubMed DOI

Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Academic radiology Feb 1, 2018
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction.
Area Under Curve Breast Parenchymal Tissue Adult Breast Neoplasms Humans Case-Control Studies Neural Networks, Computer ROC Curve Retrospective Studies Mammography Female
View on PubMed DOI

Machine learning techniques for medical diagnosis of diabetes using iris images.

Computer methods and programs in biomedicine Jan 11, 2018
BACKGROUND AND OBJECTIVE: Complementary and alternative medicine techniques have shown their potential for the treatment and diagnosis of chronical diseases like diabetes, arthritis etc. On the same time digital image processing techniques for diseas...
Humans Machine Learning Automation Iris Middle Aged Female Case-Control Studies Reproducibility of Results Diagnosis, Computer-Assisted Sensitivity and Specificity Diabetes Mellitus, Type 2 Male Image Processing, Computer-Assisted
View on PubMed DOI

Identification of candidate serum biomarkers of childhood-onset growth hormone deficiency using SWATH-MS and feature selection.

Journal of proteomics Jan 6, 2018
UNLABELLED: A typical clinical manifestation of growth hormone deficiency (GHD) is a short stature resulting from delayed growth, but GHD affects bone health, cardiovascular function and metabolic profile and therefore quality of life. Although early...
Adolescent Human Growth Hormone Child, Preschool Child Mass Spectrometry beta-Thromboglobulin Age of Onset Apolipoproteins Apolipoproteins A Algorithms Humans Biomarkers Machine Learning Female Male Case-Control Studies
View on PubMed DOI

Natural language processing of clinical notes for identification of critical limb ischemia.

International journal of medical informatics Dec 28, 2017
BACKGROUND: Critical limb ischemia (CLI) is a complication of advanced peripheral artery disease (PAD) with diagnosis based on the presence of clinical signs and symptoms. However, automated identification of cases from electronic health records (EHR...
Natural Language Processing Humans Aged Data Mining Algorithms Male Ischemia Electronic Health Records Case-Control Studies Lower Extremity Female Peripheral Arterial Disease
View on PubMed DOI
Popular Topics
Recent Journals