AIMC Topic: Female

Clear Filters Showing 19871 to 19880 of 29210 articles

Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.

Scientific reports
We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal bone marrows in MRI. This retrospective study included 467 cases, which were split into a training (n...

Machine Learning Readmission Risk Modeling: A Pediatric Case Study.

BioMed research international
BACKGROUND: Hospital readmission prediction in pediatric hospitals has received little attention. Studies have focused on the readmission frequency analysis stratified by disease and demographic/geographic characteristics but there are no predictive ...

Machine learning performance in a microbial molecular autopsy context: A cross-sectional postmortem human population study.

PloS one
BACKGROUND: The postmortem microbiome can provide valuable information to a death investigation and to the human health of the once living. Microbiome sequencing produces, in general, large multi-dimensional datasets that can be difficult to analyze ...

Hypercomplex extreme learning machine with its application in multispectral palmprint recognition.

PloS one
An extreme learning machine (ELM) is a novel training method for single-hidden layer feedforward neural networks (SLFNs) in which the hidden nodes are randomly assigned and fixed without iterative tuning. ELMs have earned widespread global interest d...

Duplicate portion sampling gives the most accurate iron intake estimate: Implications for iron status of female students.

International journal for vitamin and nutrition research. Internationale Zeitschrift fur Vitamin- und Ernahrungsforschung. Journal international de vitaminologie et de nutrition
Iron deficiency (ID) is one of the most common nutritional problems in the developing world, affecting primarily women of childbearing age. Poor dietary iron intake is a major reason of ID. Accurate measurement of iron intake is of crucial importance...

Machine Learning Analysis of Matricellular Proteins and Clinical Variables for Early Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage.

Molecular neurobiology
Although delayed cerebral ischemia (DCI) is a well-known complication after subarachnoid hemorrhage (SAH), there are no reliable biomarkers to predict DCI development. Matricellular proteins (MCPs) have been reported relevant to DCI and expected to b...

The use of natural language processing to identify Tdap-related local reactions at five health care systems in the Vaccine Safety Datalink.

International journal of medical informatics
OBJECTIVE: Local reactions are the most common vaccine-related adverse event. There is no specific diagnosis code for local reaction due to vaccination. Previous vaccine safety studies used non-specific diagnosis codes to identify potential local rea...

Head and neck squamous cell carcinoma: prediction of cervical lymph node metastasis by dual-energy CT texture analysis with machine learning.

European radiology
OBJECTIVES: This study was conducted in order to evaluate a novel risk stratification model using dual-energy CT (DECT) texture analysis of head and neck squamous cell carcinoma (HNSCC) with machine learning to (1) predict associated cervical lymphad...

Simulating Dual-Energy X-Ray Absorptiometry in CT Using Deep-Learning Segmentation Cascade.

Journal of the American College of Radiology : JACR
PURPOSE: Osteoporosis is an underdiagnosed condition despite effective screening modalities. Dual-energy x-ray absorptiometry (DEXA) screening, although recommended in clinical guidelines, remains markedly underutilized. In contrast to DEXA, CT utili...

Automatic PET cervical tumor segmentation by combining deep learning and anatomic prior.

Physics in medicine and biology
Cervical tumor segmentation on 3D FDG PET images is a challenging task because of the proximity between cervix and bladder, both of which can uptake FDG tracers. This problem makes traditional segmentation based on intensity variation methods ineffec...