AIMC Topic: Female

Clear Filters Showing 20691 to 20700 of 29210 articles

Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms.

Radiology
Purpose To develop and evaluate a supportive algorithm using deep learning for detecting cerebral aneurysms at time-of-flight MR angiography to provide a second assessment of images already interpreted by radiologists. Materials and Methods MR images...

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification.

IEEE transactions on bio-medical engineering
Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This paper proposes a joint classification-and-prediction framework based on convolutional neural networks (CNNs) for automatic sleep staging, and, subsequent...

Sparse Representation Over Learned Dictionaries on the Riemannian Manifold for Automated Grading of Nuclear Pleomorphism in Breast Cancer.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Breast cancer is found to be the most pervasive type of cancer among women. Computer aided detection and diagnosis of cancer at the initial stages can increase the chances of recovery and thus reduce the mortality rate through timely prognosis and ad...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy
We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and ...

Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome.

EBioMedicine
BACKGROUND: Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, current manual interpretation suffers from dr...

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.

Nature medicine
Sepsis is the third leading cause of death worldwide and the main cause of mortality in hospitals, but the best treatment strategy remains uncertain. In particular, evidence suggests that current practices in the administration of intravenous fluids ...

Machine-learning-based automatic identification of fetal abdominal circumference from ultrasound images.

Physiological measurement
OBJECTIVE: Obstetricians mainly use ultrasound imaging for fetal biometric measurements. However, such measurements are cumbersome. Hence, there is urgent need for automatic biometric estimation. Automated analysis of ultrasound images is complicated...

Electroencephalography-based machine learning for cognitive profiling in Parkinson's disease: Preliminary results.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Cognitive symptoms are common in patients with Parkinson's disease. Characterization of a patient's cognitive profile is an essential step toward the identification of predictors of cognitive worsening.

Therapeutic drug monitoring of levetiracetam in daily clinical practice: high-performance liquid chromatography versus immunoassay.

European journal of hospital pharmacy : science and practice
OBJECTIVES: Although levetiracetam presents an easy dosing and tolerability, therapeutic drug monitoring may be recommended in certain situations. Measurement of levetiracetam in serum plasma is commonly done by high performance liquid chromatography...