AIMC Topic: Preoperative Care

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Deep Learning for Adjacent Segment Disease at Preoperative MRI for Cervical Radiculopathy.

Radiology Sep 21, 2021
Background Patients who undergo surgery for cervical radiculopathy are at risk for developing adjacent segment disease (ASD). Identifying patients who will develop ASD remains challenging for clinicians. Purpose To develop and validate a deep learnin...
Retrospective Studies Female Reproducibility of Results Adult Sensitivity and Specificity Male Humans Middle Aged Postoperative Complications Deep Learning Magnetic Resonance Imaging Predictive Value of Tests Cervical Vertebrae Spinal Fusion Image Interpretation, Computer-Assisted Radiculopathy Preoperative Care Diskectomy Spinal Cord Diseases
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Predicting post-operative right ventricular failure using video-based deep learning.

Nature communications Aug 31, 2021
Despite progressive improvements over the decades, the rich temporally resolved data in an echocardiogram remain underutilized. Human assessments reduce the complex patterns of cardiac wall motion, to a small list of measurements of heart function. A...
Heart Failure Video Recording Postoperative Period Preoperative Care Humans Retrospective Studies Echocardiography Deep Learning Heart Ventricular Dysfunction, Right
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Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers.

World neurosurgery Nov 28, 2020
BACKGROUND: The consistency of meningioma is a factor that may influence surgical planning and the extent of resection. The aim of our study is to develop a predictive model of tumor consistency using the radiomic features of preoperative magnetic re...
Preoperative Care Intraoperative Care Meningioma Elasticity Imaging Techniques Meningeal Neoplasms Diffusion Magnetic Resonance Imaging Logistic Models Support Vector Machine Magnetic Resonance Imaging Decision Trees Bayes Theorem Supratentorial Neoplasms Humans Neural Networks, Computer Machine Learning Retrospective Studies Female Aged Male Middle Aged Pilot Projects Computational Biology
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Predicting Postoperative Mortality After Metastatic Intraspinal Neoplasm Excision: Development of a Machine-Learning Approach.

World neurosurgery Nov 16, 2020
OBJECTIVE: Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning to predict mortality. In this investigation, we use a Naïve Bayes classificatio...
Pulmonary Disease, Chronic Obstructive Male Middle Aged Risk Assessment Respiration, Artificial Weight Loss Humans Machine Learning Female Aged Odds Ratio Serum Albumin Mortality Dyspnea Preoperative Care Laminectomy Blood Coagulation Disorders Hypertension Smoking Body Mass Index Metastasectomy Bayes Theorem Spinal Neoplasms Ascites Multivariate Analysis Hypoalbuminemia
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Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

European journal of radiology Aug 28, 2020
PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade.
Multiparametric Magnetic Resonance Imaging Area Under Curve Neoplasm Grading Image Interpretation, Computer-Assisted Preoperative Care Meningioma Meningeal Neoplasms Reproducibility of Results Humans Male Middle Aged Machine Learning ROC Curve Retrospective Studies Predictive Value of Tests Female
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A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Scientific reports Jul 16, 2020
Glioblastoma is the most common malignant brain parenchymal tumor yet remains challenging to treat. The current standard of care-resection and chemoradiation-is limited in part due to the genetic heterogeneity of glioblastoma. Previous studies have i...
Humans Artificial Intelligence Mutation Aneuploidy Image Interpretation, Computer-Assisted Chromosomes, Human, Pair 7 Male Retrospective Studies Isocitrate Dehydrogenase X-linked Nuclear Protein Magnetic Resonance Imaging Preoperative Care Female Cyclin-Dependent Kinase Inhibitor p16 Chromosomes, Human, Pair 10 Sensitivity and Specificity Decision Trees Biomarkers, Tumor Glioblastoma Brain Neoplasms Gene Expression
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Single-Port Robotic Urological Surgery Using Purpose-Built Single-Port Surgical System: Single-Institutional Experience With the First 100 Cases.

Urology Mar 3, 2020
OBJECTIVES: To present a comprehensive report regarding our experience with single-port robotic surgery in our first 100 consecutive patients. We describe the diversity of procedures that can be performed with this platform as well as the challenges ...
Urologic Neoplasms Robotics Minimally Invasive Surgical Procedures Robotic Surgical Procedures Preoperative Care Conversion to Open Surgery Intraoperative Complications Urologic Surgical Procedures Outcome and Process Assessment, Health Care Humans Female Aged Male Middle Aged Postoperative Complications
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A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.

European journal of radiology Feb 13, 2020
PURPOSE: The type of pituitary adenoma (PA) cannot be clearly recognized with preoperative magnetic resonance imaging (MRI) but can be classified with immunohistochemical staining after surgery. In this study, a model to precisely immunohistochemical...
Bayes Theorem Image Interpretation, Computer-Assisted Immunohistochemistry Preoperative Care Pituitary Gland Humans Machine Learning Male Retrospective Studies Middle Aged Female Adolescent Aged Magnetic Resonance Imaging Young Adult Pituitary Neoplasms Adult Adenoma
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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Deep Learning Neoplasm Invasiveness Outcome Assessment, Health Care Area Under Curve Humans Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Reproducibility of Results Neural Networks, Computer Japan Preoperative Care Artificial Intelligence Aged Endoscopic Mucosal Resection Retrospective Studies Aged, 80 and over Female Sensitivity and Specificity Male Middle Aged
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Automatic detection of perforators for microsurgical reconstruction.

Breast (Edinburgh, Scotland) Jan 12, 2020
The deep inferior epigastric perforator (DIEP) is the most commonly used free flap in mastectomy reconstruction. Preoperative imaging techniques are routinely used to detect location, diameter and course of perforators, with direct intervention from ...
Preoperative Care Humans Free Tissue Flaps Artificial Intelligence Perforator Flap Epigastric Arteries Software Female Pilot Projects Image Processing, Computer-Assisted Mammaplasty
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