AIMC Topic: Sensitivity and Specificity
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Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.
Frontiers in endocrinology
Nov 2, 2021
fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does not guarantee success. Frozen embryo transfer (FET) is an important supplement to IVF-ET. Many factor...
Machine Learning for Predicting Motor Improvement After Acute Subcortical Infarction Using Baseline Whole Brain Volumes.
Neurorehabilitation and neural repair
Nov 1, 2021
Neuroimaging biomarkers are valuable predictors of motor improvement after stroke, but there is a gap between published evidence and clinical usage. In this work, we aimed to investigate whether machine learning techniques, when applied to a combin...
Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy.
JAMA network open
Nov 1, 2021
IMPORTANCE: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; however, many patients do not receive their recommended annual diabetic eye examinations, primarily owi...
Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy.
Scientific reports
Oct 27, 2021
The prediction of anatomical structures within the surgical field by artificial intelligence (AI) is expected to support surgeons' experience and cognitive skills. We aimed to develop a deep-learning model to automatically segment loose connective ti...
Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Oct 20, 2021
BACKGROUND: Attenuation correction can improve the quantitative accuracy of single-photon emission computed tomography (SPECT) images. Existing SPECT-only systems normally can only provide non-attenuation corrected (NC) images which are susceptible t...
Utility of a Deep Learning Algorithm for Detection of Reticular Opacity on Chest Radiography in Patients With Interstitial Lung Disease.
AJR. American journal of roentgenology
Oct 20, 2021
Deep learning has been heavily explored for pulmonary nodule detection on chest radiographs. Detection of reticular opacity in interstitial lung disease (ILD) is challenging and may also benefit from a deep learning algorithm (DLA). The purpose of ...
Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis.
Radiology
Oct 19, 2021
Background Advances in computer processing and improvements in data availability have led to the development of machine learning (ML) techniques for mammographic imaging. Purpose To evaluate the reported performance of stand-alone ML applications for...
Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network.
Scientific reports
Oct 14, 2021
Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detection and the prognosis is poor. In this paper, 910 benign and 934 malignant (110 TN and 824 NTN) B-mode breast ultrasound images were collected. A Resn...
Prediction of viral symptoms using wearable technology and artificial intelligence: A pilot study in healthcare workers.
PloS one
Oct 14, 2021
Conventional testing and diagnostic methods for infections like SARS-CoV-2 have limitations for population health management and public policy. We hypothesize that daily changes in autonomic activity, measured through off-the-shelf technologies toget...
Artificial intelligence on COVID-19 pneumonia detection using chest xray images.
PloS one
Oct 14, 2021
Recent studies show the potential of artificial intelligence (AI) as a screening tool to detect COVID-19 pneumonia based on chest x-ray (CXR) images. However, issues on the datasets and study designs from medical and technical perspectives, as well a...
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