AI Medical Compendium Topic

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Automation

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Automated laryngeal mass detection algorithm for home-based self-screening test based on convolutional neural network.

Biomedical engineering online
BACKGROUND: Early detection of laryngeal masses without periodic visits to hospitals is essential for improving the possibility of full recovery and the long-term survival ratio after prompt treatment, as well as reducing the risk of clinical infecti...

Converging global crises are forcing the rapid adoption of disruptive changes in drug discovery.

Drug discovery today
Spiralling research costs combined with urgent pressures from the Coronavirus 2019 (COVID-19) pandemic and the consequences of climate disruption are forcing changes in drug discovery. Increasing the predictive power of in vitro human assays and usin...

PeriorbitAI: Artificial Intelligence Automation of Eyelid and Periorbital Measurements.

American journal of ophthalmology
PURPOSE: To develop a deep learning semantic segmentation network to automate the assessment of 8 periorbital measurements DESIGN: Development and validation of an artificial intelligence (AI) segmentation algorithm METHODS: A total of 418 photograph...

Applications of artificial intelligence and machine learning approaches in echocardiography.

Echocardiography (Mount Kisco, N.Y.)
Artificial intelligence and machine learning approaches have become increasingly applied in the field of echocardiography to streamline diagnostic and prognostic assessments, and to support treatment decisions. Artificial intelligence and machine lea...

Learning deep features for dead and living breast cancer cell classification without staining.

Scientific reports
Automated cell classification in cancer biology is a challenging topic in computer vision and machine learning research. Breast cancer is the most common malignancy in women that usually involves phenotypically diverse populations of breast cancer ce...

Predicting sex from retinal fundus photographs using automated deep learning.

Scientific reports
Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. Herein we present the development of a deep learning model by clinicians without coding, which predicts reporte...

An open-source semi-automated robotics pipeline for embryo immunohistochemistry.

Scientific reports
A significant challenge for developmental systems biology is balancing throughput with controlled conditions that minimize experimental artifacts. Large-scale developmental screens such as unbiased mutagenesis surveys have been limited in their appli...

Red blood cell phenotyping from 3D confocal images using artificial neural networks.

PLoS computational biology
The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fin...

Assistance from Automated ASPECTS Software Improves Reader Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with...

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density.

Scientific reports
Arthritis patients develop hand bone loss, which leads to destruction and functional impairment of the affected joints. High resolution peripheral quantitative computed tomography (HR-pQCT) allows the quantification of volumetric bone mineral density...