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https://www.readbyqxmd.com/read/28750949/a-machine-learning-approach-for-real-time-modelling-of-tissue-deformation-in-image-guided-neurosurgery
#1
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 24, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28691131/a-survey-of-context-recognition-in-surgery
#2
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
#3
Frank Cornelis Bennis, Björn Van der Ster, Johannes Van Lieshout, Peter Andriessen, Tammo Delhaas
Traditional patient monitoring during surgery include 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) in an early stage. Approach: Twenty-eight healthy subjects (age 18-50 yr) were included. Lower body negative pressure (-50 mmHg) was applied to induce central hypovolemia until onset of pre-syncope...
July 3, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28660725/automated-robot-assisted-surgical-skill-evaluation-predictive-analytics-approach
#4
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
#5
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
#6
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
#7
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
#8
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
#9
Md N Karim, Christopher M Reid, Andrew Cochrane, Lavinia Tran, Mohammed Alramadan, Md 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...
May 11, 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
#10
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
https://www.readbyqxmd.com/read/28434153/machine-learning-xgboost-analysis-of-language-networks-to-classify-patients-with-epilepsy
#11
L Torlay, M Perrone-Bertolotti, E Thomas, M Baciu
Our goal was to apply a statistical approach to allow the identification of atypical language patterns and to differentiate patients with epilepsy from healthy subjects, based on their cerebral activity, as assessed by functional MRI (fMRI). Patients with focal epilepsy show reorganization or plasticity of brain networks involved in cognitive functions, inducing 'atypical' (compared to 'typical' in healthy people) brain profiles. Moreover, some of these patients suffer from drug-resistant epilepsy, and they undergo surgery to stop seizures...
April 22, 2017: Brain Informatics
https://www.readbyqxmd.com/read/28368992/validation-of-an-objective-keratoconus-detection-system-implemented-in-a-scheimpflug-tomographer-and-comparison-with-other-methods
#12
Irene Ruiz Hidalgo, Jos J Rozema, Alain Saad, Damien Gatinel, Pablo Rodriguez, Nadia Zakaria, Carina Koppen
PURPOSE: To validate a recently developed program for automatic and objective keratoconus detection (Keratoconus Assistant [KA]) by applying it to a new population and comparing it with other methods described in the literature. METHODS: KA uses machine learning and 25 Pentacam-derived parameters to classify eyes into subgroups, such as keratoconus, keratoconus suspect, postrefractive surgery, and normal eyes. To validate this program, it was applied to 131 eyes diagnosed separately by experienced corneal specialists from 2 different centers (Fondation Rothschild, Paris, and Antwerp University Hospital [UZA])...
June 2017: Cornea
https://www.readbyqxmd.com/read/28365240/using-electronic-health-records-to-build-an-ophthalmologic-data-warehouse-and-visualize-patients-data
#13
Karsten U Kortüm, Michael Müller, Christoph Kern, Alexander Babenko, Wolfgang J Mayer, Anselm Kampik, Thomas C Kreutzer, Siegfried Priglinger, Christoph Hirneiss
PURPOSE: To develop a near-real-time data warehouse (DW) in an academic ophthalmologic center to gain scientific use of increasing digital data from electronic medical records (EMR) and diagnostic devices. DESIGN: Database development. METHODS: Specific macular clinic user interfaces within the institutional hospital information system were created. Orders for imaging modalities were sent by an EMR-linked picture-archiving and communications system to the respective devices...
June 2017: American Journal of Ophthalmology
https://www.readbyqxmd.com/read/28333183/machine-learning-algorithms-for-objective-remission-and-clinical-outcomes-with-thiopurines
#14
Akbar K Waljee, Kay Sauder, Anand Patel, Sandeep Segar, Boang Liu, Yiwei Zhang, Ji Zhu, Ryan W Stidham, Ulysses Balis, Peter D R Higgins
Background and Aims: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimising thiopurine therapy for inflammatory bowel disease [IBD] has proved difficult. Current methods using 6-thioguanine nucleotide [6-TGN] metabolites have failed in randomized controlled trials [RCTs], and have not been used to predict objective remission [OR]. Our aims were to: 1) develop machine learning algorithms [MLA] using laboratory values and age to identify patients in objective remission on thiopurines; and 2) determine whether achieving algorithm-predicted objective remission resulted in fewer clinical events per year...
March 14, 2017: Journal of Crohn's & Colitis
https://www.readbyqxmd.com/read/28319476/anesthesia-in-patients-with-infectious-disease-caused-by-multi-drug-resistant-bacteria
#15
Sharon Einav, Yonit Wiener-Well
PURPOSE OF REVIEW: Up to 50% of specific bacterial strains in healthcare admission facilities are multi-drug resistant organisms (MDROs). Involvement of anesthesiologists in management of patients carrying/at risk of carrying MDROs may decrease transmission in the Operating Room (OR). RECENT FINDINGS: Anesthesiologists, their work area and tools have all been implicated in MDRO outbreaks. Causes include contamination of external ventilation circuits and noncontribution of filters to prevention, inappropriate decontamination procedures for nondisposable equipment (e...
June 2017: Current Opinion in Anaesthesiology
https://www.readbyqxmd.com/read/28268919/non-invasive-optical-imaging-techniques-for-burn-injured-tissue-detection-for-debridement-surgery
#16
Juan Heredia-Juesas, Jeffrey E Thatcher, Yang Lu, John J Squiers, Darlene King, Wensheng Fan, J Michael DiMaio, Jose A Martinez-Lorenzo
Burn debridement is a challenging technique that requires significant skill to identify regions requiring excision and appropriate excision depth. A machine learning tool is being developed in order to assist surgeons by providing a quantitative assessment of burn-injured tissue. Three noninvasive optical imaging techniques capable of distinguishing between four kinds of tissue-healthy skin, viable wound bed, deep burn, and shallow burn-during serial burn debridement in a porcine model are presented in this paper...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227123/non-invasive-optical-imaging-techniques-for-burn-injured-tissue-detection-for-debridement-surgery
#17
Juan Heredia-Juesas, Jeffrey E Thatcher, Yang Lu, John J Squiers, Darlene King, Wensheng Fan, J Michael DiMaio, Jose A Martinez-Lorenzo, Juan Heredia-Juesas, Jeffrey E Thatcher, Yang Lu, John J Squiers, Darlene King, Wensheng Fan, J Michael DiMaio, Jose A Martinez-Lorenzo, Jeffrey E Thatcher, Darlene King, Jose A Martinez-Lorenzo, Wensheng Fan, Juan Heredia-Juesas, Yang Lu, John J Squiers
Burn debridement is a challenging technique that requires significant skill to identify regions requiring excision and appropriate excision depth. A machine learning tool is being developed in order to assist surgeons by providing a quantitative assessment of burn-injured tissue. Three noninvasive optical imaging techniques capable of distinguishing between four kinds of tissue-healthy skin, viable wound bed, deep burn, and shallow burn-during serial burn debridement in a porcine model are presented in this paper...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28166392/interictal-network-synchrony-and-local-heterogeneity-predict-epilepsy-surgery-outcome-among-pediatric-patients
#18
Samuel B Tomlinson, Brenda E Porter, Eric D Marsh
OBJECTIVE: Epilepsy is a disorder of aberrant cortical networks. Researchers have proposed that characterizing presurgical network connectivity may improve the surgical management of intractable seizures, but few studies have rigorously examined the relationship between network activity and surgical outcome. In this study, we assessed whether local and global measures of network activity differentiated patients with favorable (seizure-free) versus unfavorable (seizure-persistent) surgical outcomes...
March 2017: Epilepsia
https://www.readbyqxmd.com/read/28155719/contralateral-artery-enlargement-predicts-carotid-plaque-progression-based-on-machine-learning-algorithm-models-in-apoe-mice
#19
Bing Li, Yun Jiao, Cong Fu, Bo Xie, Genshan Ma, Gaojun Teng, Yuyu Yao
BACKGROUND: This study specifically focused on anatomical MRI characterization of the low shear stress-induced atherosclerotic plaque in mice. We used machine learning algorithms to analyze multiple correlation factors of plaque to generate predictive models and to find the predictive factor for vulnerable plaque. METHODS: Branches of the left carotid artery in apoE(-/-) and C57BL/6J mice were ligated to produce the partial left carotid artery model. Before surgery, and 7, 14, and 28 days after surgery, in vivo serial MRI measurements of carotid artery diameter were obtained...
December 28, 2016: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28126242/artificial-intelligence-in-medicine
#20
REVIEW
Pavel Hamet, Johanne Tremblay
Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation...
April 2017: Metabolism: Clinical and Experimental
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