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https://www.readbyqxmd.com/read/29042101/machine-learning-phenotypic-classification-of-bicuspid-aortopathy
#1
Charles M Wojnarski, Eric E Roselli, Jay J Idrees, Yuanjia Zhu, Theresa A Carnes, Ashley M Lowry, Patrick H Collier, Brian Griffin, John Ehrlinger, Eugene H Blackstone, Lars G Svensson, Bruce W Lytle
BACKGROUND: Bicuspid aortic valves (BAV) are associated with incompletely characterized aortopathy. Our objectives were to identify distinct patterns of aortopathy using machine-learning methods and characterize their association with valve morphology and patient characteristics. METHODS: We analyzed preoperative 3-dimensional computed tomography reconstructions for 656 patients with BAV undergoing ascending aorta surgery between January 2002 and January 2014. Unsupervised partitioning around medoids was used to cluster aortic dimensions...
September 14, 2017: Journal of Thoracic and Cardiovascular Surgery
https://www.readbyqxmd.com/read/29039725/high-risk-breast-lesions-a-machine-learning-model-to-predict-pathologic-upgrade-and-reduce-unnecessary-surgical-excision
#2
Manisha Bahl, Regina Barzilay, Adam B Yedidia, Nicholas J Locascio, Lili Yu, Constance D Lehman
Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgical excision to be distinguished from HRLs that are at low risk for upgrade to cancer at surgery and thus could be surveilled. Materials and Methods Consecutive patients with biopsy-proven HRLs who underwent surgery or at least 2 years of imaging follow-up from June 2006 to April 2015 were identified. A random forest machine learning model was developed to identify HRLs at low risk for upgrade to cancer...
October 17, 2017: Radiology
https://www.readbyqxmd.com/read/29016439/examining-the-ability-of-artificial-neural-networks-machine-learning-models-to-accurately-predict-complications-following-posterior-lumbar-spine-fusion
#3
Jun S Kim, Robert K Merrill, Varun Arvind, Deepak Kaji, Sara D Pasik, Chuma C Nwachukwu, Luilly Vargas, Nebiyu S Osman, Eric K Oermann, John M Caridi, Samuel K Cho
STUDY DESIGN: Cross-sectional database study. OBJECTIVE: To train and validate machine learning models to identify risk factors for complications following posterior lumbar spine fusion. SUMMARY OF BACKGROUND DATA: Machine learning models such as artificial neural networks (ANNs) are valuable tools for analyzing and interpreting large and complex datasets. ANNs have yet to be used for risk factor analysis in orthopedic surgery. METHODS: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried for patients who underwent posterior lumbar spine fusion...
October 9, 2017: Spine
https://www.readbyqxmd.com/read/28990168/automated-analysis-of-seizure-semiology-and-brain-electrical-activity-in-presurgery-evaluation-of-epilepsy-a-focused-survey
#4
REVIEW
David Ahmedt-Aristizabal, Clinton Fookes, Sasha Dionisio, Kien Nguyen, João Paulo S Cunha, Sridha Sridharan
Epilepsy being one of the most prevalent neurological disorders, affecting approximately 50 million people worldwide, and with almost 30-40% of patients experiencing partial epilepsy being nonresponsive to medication, epilepsy surgery is widely accepted as an effective therapeutic option. Presurgical evaluation has advanced significantly using noninvasive techniques based on video monitoring, neuroimaging, and electrophysiological and neuropsychological tests; however, certain clinical settings call for invasive intracranial recordings such as stereoelectroencephalography (SEEG), aiming to accurately map the eloquent brain networks involved during a seizure...
October 9, 2017: Epilepsia
https://www.readbyqxmd.com/read/28987701/comparison-of-perioperative-automated-versus-manual-two-dimensional-tumor-analysis-in-glioblastoma-patients
#5
Frauke Kellner-Weldon, Christoph Stippich, Roland Wiest, Vera Lehmann, Raphael Meier, Jürgen Beck, Philippe Schucht, Andreas Raabe, Mauricio Reyes, Andrea Bink
OBJECTIVES: Current recommendations for the measurement of tumor size in glioblastoma continue to employ manually measured 2D product diameters of enhancing tumor. To overcome the rater dependent variability, this study aimed to evaluate the potential of automated 2D tumor analysis (ATA) compared to highly experienced rater teams in the workup of pre- and postoperative image interpretation in a routine clinical setting. MATERIALS AND METHODS: From 92 patients with newly diagnosed GB and performed surgery, manual rating of the sum product diameter (SPD) of enhancing tumor on magnetic resonance imaging (MRI) contrast enhanced T1w was compared to automated machine learning-based tumor analysis using FLAIR, T1w, T2w and contrast enhanced T1w...
October 2017: European Journal of Radiology
https://www.readbyqxmd.com/read/28986230/machine-learning-and-neurosurgical-outcome-prediction-a-systematic-review
#6
REVIEW
Joeky T Senders, Patrick C Staples, Aditya V Karhade, Mark M Zaki, William B Gormley, Marike L D Broekman, Timothy R Smith, Omar Arnaout
OBJECTIVE: Accurate measurement of surgical outcomes is highly desirable to optimize surgical decision-making. An important element of surgical decision making is identification of the patient cohort that will benefit from surgery prior to the intervention. Machine learning (ML) enables computers to learn from previous data to make accurate predictions on new data. In this systematic review, we evaluate the potential of ML for neurosurgical outcome prediction. METHODS: A systematic search in the Pubmed and Embase databases was performed to identify all potential relevant studies up to January 1, 2017...
October 3, 2017: World Neurosurgery
https://www.readbyqxmd.com/read/28960172/resting-state-functional-magnetic-resonance-imaging-for-surgical-planning-in-pediatric-patients-a-preliminary-experience
#7
Jarod L Roland, Natalie Griffin, Carl D Hacker, Ananth K Vellimana, S Hassan Akbari, Joshua S Shimony, Matthew D Smyth, Eric C Leuthardt, David D Limbrick
OBJECTIVE Cerebral mapping for surgical planning and operative guidance is a challenging task in neurosurgery. Pediatric patients are often poor candidates for many modern mapping techniques because of inability to cooperate due to their immature age, cognitive deficits, or other factors. Resting-state functional MRI (rs-fMRI) is uniquely suited to benefit pediatric patients because it is inherently noninvasive and does not require task performance or significant cooperation. Recent advances in the field have made mapping cerebral networks possible on an individual basis for use in clinical decision making...
September 29, 2017: Journal of Neurosurgery. Pediatrics
https://www.readbyqxmd.com/read/28882391/-evaluation-of-surgical-simulation-sessions-of-the-french-society-of-ophthalmology-a-new-surgical-instruction-method
#8
H El Chehab, E Agard, C Dot
INTRODUCTION: Since 2013, at the French society of ophthalmology (FSO) meetings, two simulators for intraocular surgeries have been available. The goal of this study was to assess the satisfaction of the participants in these organized training sessions. MATERIALS AND METHODS: A questionnaire was mailed to participants in the FSO sessions as well as those carried out during the annual congress. This questionnaire collected data on the participants and the practical modalities of the sessions, and assessed participants' feelings and satisfaction with these sessions...
October 2017: Journal Français D'ophtalmologie
https://www.readbyqxmd.com/read/28880333/predicting-refractive-surgery-outcome-machine-learning-approach-with-big-data
#9
Asaf Achiron, Zvi Gur, Uri Aviv, Assaf Hilely, Michael Mimouni, Lily Karmona, Lior Rokach, Igor Kaiserman
PURPOSE: To develop a decision forest for prediction of laser refractive surgery outcome. METHODS: Data from consecutive cases of patients who underwent LASIK or photorefractive surgeries during a 12-year period in a single center were assembled into a single dataset. Training of machine-learning classifiers and testing were performed with a statistical classifier algorithm. The decision forest was created by feature vectors extracted from 17,592 cases and 38 clinical parameters for each patient...
September 1, 2017: Journal of Refractive Surgery
https://www.readbyqxmd.com/read/28876574/holding-the-torch-up-high-a-medical-historical-evaluation-of-surgical-advances-during-the-great-war-1914-1918-in-memory-of-those-that-served-and-fell
#10
G Scharf
"How wide and varied is the experience of the battlefield and how fertile the blood of warriors in raising good surgeons" Sir Clifford Allbutt (1898). With these sentiments of the medical lessons learned in war and conflict, with the background of the poem of "In Flanders Field", written by a doctor who had South African War connections, reasons (the Somme and third Ypres battles) will be given that this was indeed a "GREAT WAR" as the world history, weapons, strategy, tactics and wounding patterns had changed dramatically...
September 2017: South African Journal of Surgery. Suid-Afrikaanse Tydskrif Vir Chirurgie
https://www.readbyqxmd.com/read/28750949/a-machine-learning-approach-for-real-time-modelling-of-tissue-deformation-in-image-guided-neurosurgery
#11
Michele Tonutti, Gauthier Gras, Guang-Zhong Yang
OBJECTIVES: Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augmented reality (AR) applications. Current deformation models are characterised by a trade-off between accuracy and computational speed. We propose an approach to derive a patient-specific deformation model for brain pathologies by combining the results of pre-computed finite element method (FEM) simulations with machine learning algorithms...
July 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28691131/a-survey-of-context-recognition-in-surgery
#12
Igor Pernek, Alois Ferscha
With the introduction of operating rooms of the future context awareness has gained importance in the surgical environment. This paper organizes and reviews different approaches for recognition of context in surgery. Major electronic research databases were queried to obtain relevant publications submitted between the years 2010 and 2015. Three different types of context were identified: (i) the surgical workflow context, (ii) surgeon's cognitive and (iii) technical state context. A total of 52 relevant studies were identified and grouped based on the type of context detected and sensors used...
July 10, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28671554/a-machine-learning-based-analysis-for-the-recognition-of-progressive-central-hypovolemia
#13
Frank C Bennis, Björn Jp van der Ster, Johannes J van Lieshout, Peter Andriessen, Tammo Delhaas
OBJECTIVE: Traditional patient monitoring during surgery includes heart rate (HR), blood pressure (BP) and peripheral oxygen saturation. However, their use as predictors for central hypovolemia is limited, which may lead to cerebral hypoperfusion. The aim of this study was to develop a monitoring model that can indicate a decrease in central blood volume (CBV) at an early stage. APPROACH: Twenty-eight healthy subjects (aged 18-50 years) were included. Lower body negative pressure (-50 mmHg) was applied to induce central hypovolemia until the onset of pre-syncope...
August 21, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28660725/automated-robot-assisted-surgical-skill-evaluation-predictive-analytics-approach
#14
Mahtab J Fard, Sattar Ameri, R Darin Ellis, Ratna B Chinnam, Abhilash K Pandya, Michael D Klein
BACKGROUND: Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predictive framework for objective skill assessment based on movement trajectory data. Our aim is to build a classification framework to automatically evaluate the performance of surgeons with different levels of expertise. METHODS: Eight global movement features are extracted from movement trajectory data captured by a da Vinci robot for surgeons with two levels of expertise - novice and expert...
June 29, 2017: International Journal of Medical Robotics + Computer Assisted Surgery: MRCAS
https://www.readbyqxmd.com/read/28654820/the-potential-value-of-preoperative-mri-texture-and-shape-analysis-in-grading-meningiomas-a-preliminary-investigation
#15
Peng-Fei Yan, Ling Yan, Ting-Ting Hu, Dong-Dong Xiao, Zhen Zhang, Hong-Yang Zhao, Jun Feng
OBJECT: Preoperative knowledge of meningioma grade is essential for planning treatment and surgery. The purpose of this study was to investigate the diagnostic value of MRI texture and shape analysis in grading meningiomas. METHODS: A surgical database was reviewed to identify meningioma patients who had undergone tumor resection between January 2015 and December 2016. Preoperative MR images were retrieved and analyzed. Texture and shape analysis was conducted to quantitatively evaluate tumor heterogeneity and morphology...
August 2017: Translational Oncology
https://www.readbyqxmd.com/read/28624625/a-formalin-fixed-paraffin-embedded-ffpe-based-prognostic-signature-to-predict-metastasis-in-clinically-low-risk-stage-i-ii-microsatellite-stable-colorectal-cancer
#16
Yee Syuen Low, Christopher Blöcker, John R McPherson, See Aik Tang, Ying Ying Cheng, Joyner Y S Wong, Clarinda Chua, Tony K H Lim, Choong Leong Tang, Min Hoe Chew, Patrick Tan, Iain B Tan, Steven G Rozen, Peh Yean Cheah
Approximately 20% early-stage (I/II) colorectal cancer (CRC) patients develop metastases despite curative surgery. We aim to develop a formalin-fixed and paraffin-embedded (FFPE)-based predictor of metastases in early-stage, clinically-defined low risk, microsatellite-stable (MSS) CRC patients. We considered genome-wide mRNA and miRNA expression and mutation status of 20 genes assayed in 150 fresh-frozen tumours with known metastasis status. We selected 193 genes for further analysis using NanoString nCounter arrays on corresponding FFPE tumours...
September 10, 2017: Cancer Letters
https://www.readbyqxmd.com/read/28521616/a-10-gene-classifier-for-indeterminate-thyroid-nodules-development-and-multicenter-accuracy-study
#17
Hernán E González, José R Martínez, Sergio Vargas-Salas, Antonieta Solar, Loreto Veliz, Francisco Cruz, Tatiana Arias, Soledad Loyola, Eleonora Horvath, Hernán Tala, Eufrosina Traipe, Manuel Meneses, Luis Marín, Nelson Wohllk, René E Diaz, Jesús Véliz, Pedro Pineda, Patricia Arroyo, Natalia Mena, Milagros Bracamonte, Giovanna Miranda, Elsa Bruce, Soledad Urra
BACKGROUND: In most of the world, diagnostic surgery remains the most frequent approach for indeterminate thyroid cytology. Although several molecular tests are available for testing in centralized commercial laboratories in the United States, there are no available kits for local laboratory testing. The aim of this study was to develop a prototype in vitro diagnostic (IVD) gene classifier for the further characterization of nodules with an indeterminate thyroid cytology. METHODS: In a first stage, the expression of 18 genes was determined by quantitative polymerase chain reaction (qPCR) in a broad histopathological spectrum of 114 fresh-tissue biopsies...
August 2017: Thyroid: Official Journal of the American Thyroid Association
https://www.readbyqxmd.com/read/28516300/predicting-surgical-skill-from-the-first-n-seconds-of-a-task-value-over-task-time-using-the-isogony-principle
#18
Anna French, Thomas S Lendvay, Robert M Sweet, Timothy M Kowalewski
PURPOSE: Most evaluations of surgical workflow or surgeon skill use simple, descriptive statistics (e.g., time) across whole procedures, thereby deemphasizing critical steps and potentially obscuring critical inefficiencies or skill deficiencies. In this work, we examine off-line, temporal clustering methods that chunk training procedures into clinically relevant surgical tasks or steps during robot-assisted surgery. METHODS: Features calculated from the isogony principle are used to train four common machine learning algorithms from dry-lab laparoscopic data gathered from three common training exercises...
July 2017: International Journal of Computer Assisted Radiology and Surgery
https://www.readbyqxmd.com/read/28497663/mortality-risk-prediction-models-for-coronary-artery-bypass-graft-surgery-current-scenario-and-future-direction
#19
REVIEW
Mohammed N Karim, Christopher M Reid, Andrew Cochrane, Lavinia Tran, Mohammed Alramadan, Mohammed N Hossain, Baki Billah
INTRODUCTION: Many risk prediction models are currently in use for predicting short-term mortality following coronary artery bypass graft (CABG) surgery. This review critically appraised the methods that were used for developing these models to assess their applicability in current practice setting as well as for the necessity of up-gradation. EVIDENCE ACQUISITION: Medline via Ovid was searched for articles published between 1946 and 2016 and EMBASE via Ovid between 1974 and 2016 to identify risk prediction models for CABG...
December 2017: Journal of Cardiovascular Surgery
https://www.readbyqxmd.com/read/28483984/machine-learning-to-support-decision-making-for-cardiac-surgery-during-the-acute-phase-of-infective-endocarditis
#20
EDITORIAL
Erwan Donal, Erwan Flecher, Pierre Tattevin
No abstract text is available yet for this article.
May 8, 2017: Heart: Official Journal of the British Cardiac Society
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