AIMC Topic: Female

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AF-SENet: Classification of Cancer in Cervical Tissue Pathological Images Based on Fusing Deep Convolution Features.

Sensors (Basel, Switzerland)
Cervical cancer is the fourth most common cancer in the world. Whole-slide images (WSIs) are an important standard for the diagnosis of cervical cancer. Missed diagnoses and misdiagnoses often occur due to the high similarity in pathological cervical...

Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.

Ophthalmology
PURPOSE: Rule-based approaches to determining glaucoma progression from visual fields (VFs) alone are discordant and have tradeoffs. To detect better when glaucoma progression is occurring, we used a longitudinal data set of merged VF and clinical da...

Anastomotic Leak is Increased With Infection After Colectomy: Machine Learning-Augmented Propensity Score Modified Analysis of 46 735 Patients.

The American surgeon
BACKGROUND: infection (CDI) is now the most common cause of healthcare-associated infections, with increasing prevalence, severity, and mortality of nosocomial and community-acquired CDI which makes up approximately one third of all CDI. There are a...

Segmentation of Chronic Subdural Hematomas Using 3D Convolutional Neural Networks.

World neurosurgery
OBJECTIVE: Chronic subdural hematomas (cSDHs) are an increasingly prevalent neurologic disease that often requires surgical intervention to alleviate compression of the brain. Management of cSDHs relies heavily on computed tomography (CT) imaging, an...

Machine Learning Algorithms Predict Clinically Significant Improvements in Satisfaction After Hip Arthroscopy.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To develop machine learning algorithms to predict failure to achieve clinically significant satisfaction after hip arthroscopy.

Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing.

Journal of emergency nursing
INTRODUCTION: Triage is critical to mitigating the effect of increased volume by determining patient acuity, need for resources, and establishing acuity-based patient prioritization. The purpose of this retrospective study was to determine whether hi...

The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood.

Neuroscience letters
BACKGROUND: Schizophrenia (SCZ) is a highly heritable mental disorder with a substantial disease burden. Machine learning (ML) method can be used to identify individuals with SCZ on the basis of blood gene expression data with high accuracy.

Characterization of Antiphospholipid Syndrome Atherothrombotic Risk by Unsupervised Integrated Transcriptomic Analyses.

Arteriosclerosis, thrombosis, and vascular biology
OBJECTIVE: Our aim was to characterize distinctive clinical antiphospholipid syndrome phenotypes and identify novel microRNA (miRNA)-mRNA-intracellular signaling regulatory networks in monocytes linked to cardiovascular disease. Approach and Results:...