AIMC Topic: Feasibility Studies

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Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Nature communications Jan 29, 2021
Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. We develop an artifici...
Feasibility Studies Data Mining Early Diagnosis Time Factors ROC Curve Predictive Value of Tests Clinical Decision Rules Machine Learning Intensive Care Units Electronic Health Records Severity of Illness Index Sepsis Risk Assessment Prevalence Humans
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Feasibility study to improve deep learning in OCT diagnosis of rare retinal diseases with few-shot classification.

Medical & biological engineering & computing Jan 25, 2021
Deep learning (DL) has been successfully applied to the diagnosis of ophthalmic diseases. However, rare diseases are commonly neglected due to insufficient data. Here, we demonstrate that few-shot learning (FSL) using a generative adversarial network...
Deep Learning Tomography, Optical Coherence Feasibility Studies Retinal Diseases Humans Neural Networks, Computer Rare Diseases
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Deep Learning Approach to Parse Eligibility Criteria in Dietary Supplements Clinical Trials Following OMOP Common Data Model.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Dietary supplements (DSs) have been widely used in the U.S. and evaluated in clinical trials as potential interventions for various diseases. However, many clinical trials face challenges in recruiting enough eligible patients in a timely fashion, ca...
Deep Learning Humans Clinical Trials as Topic Natural Language Processing Models, Theoretical Databases, Factual Feasibility Studies Dietary Supplements Partnership Practice Electronic Health Records Patient Selection
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Feasibility of a deep learning-based method for automated localization of pelvic floor landmarks using stress MR images.

International urogynecology journal Jan 21, 2021
INTRODUCTION AND HYPOTHESIS: Magnetic resonance imaging (MRI) plays an important role in assessing pelvic organ prolapse (POP), and automated pelvic floor landmark localization potentially accelerates MRI-based measurements of POP. Herein, we aimed t...
Pelvic Organ Prolapse Magnetic Resonance Imaging Humans Feasibility Studies Deep Learning Pelvic Floor
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The 3D reconstructed skin micronucleus assay using imaging flow cytometry and deep learning: A proof-of-principle investigation.

Mutation research. Genetic toxicology and environmental mutagenesis Jan 20, 2021
The reconstructed skin micronucleus (RSMN) assay was developed in 2006, as an in vitro alternative for genotoxicity evaluation of dermally applied chemicals or products. In the years since, significant progress has been made in the optimization of th...
Mitomycin Skin, Artificial Predictive Value of Tests Proof of Concept Study Flow Cytometry Micronucleus Tests Skin Mutagenicity Tests Tissue Scaffolds False Positive Reactions Feasibility Studies Models, Biological Automation, Laboratory Deep Learning Image Processing, Computer-Assisted Humans Artificial Intelligence Software
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A deep learning approach to evaluate the feasibility of enzymatic reactions generated by retrobiosynthesis.

Biotechnology journal Jan 18, 2021
Retrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective metho...
Deep Learning Feasibility Studies Biosynthetic Pathways Metabolic Engineering Neural Networks, Computer
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Robot-Assisted Carotid Artery Stenting: A Safety and Feasibility Study.

Cardiovascular and interventional radiology Jan 14, 2021
PURPOSE: Endovascular robotics is an emerging technology within the developing field of medical robotics. This was a prospective evaluation to assess safety and feasibility of robotic-assisted carotid artery stenting.
Feasibility Studies Stents Humans Carotid Artery, Common Prospective Studies Vascular Surgical Procedures Aged, 80 and over Middle Aged Male Treatment Outcome Female Robotics Aged Computed Tomography Angiography Carotid Stenosis
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Feasibility of automated planning for whole-brain radiation therapy using deep learning.

Journal of applied clinical medical physics Dec 19, 2020
PURPOSE: The purpose of this study was to develop automated planning for whole-brain radiation therapy (WBRT) using a U-net-based deep-learning model for predicting the multileaf collimator (MLC) shape bypassing the contouring processes.
Radiotherapy Planning, Computer-Assisted Cranial Irradiation Humans Brain Neoplasms Brain Deep Learning Feasibility Studies
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Reducing scan time of paediatric Tc-DMSA SPECT via deep learning.

Clinical radiology Dec 16, 2020
AIM: To investigate the feasibility of reducing the scan time of paediatric technetium 99m (Tc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.
Tomography, Emission-Computed, Single-Photon Humans Technetium Tc 99m Dimercaptosuccinic Acid Male Infant Time Factors Kidney Child, Preschool Deep Learning Kidney Diseases Child Feasibility Studies Adolescent Retrospective Studies Female Sensitivity and Specificity
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Recent advances in constraint and machine learning-based metabolic modeling by leveraging stoichiometric balances, thermodynamic feasibility and kinetic law formalisms.

Metabolic engineering Dec 10, 2020
Understanding the governing principles behind organisms' metabolism and growth underpins their effective deployment as bioproduction chassis. A central objective of metabolic modeling is predicting how metabolism and growth are affected by both exter...
Machine Learning Models, Biological Kinetics Thermodynamics Feasibility Studies
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