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Machine learning surgery

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https://www.readbyqxmd.com/read/29215501/predictive-modeling-for-blood-transfusion-following-adult-spinal-deformity-surgery-a-tree-based-machine-learning-approach
#1
Wesley M Durand, J Mason DePasse, Alan H Daniels
STUDY DESIGN: Retrospective cohort study. OBJECTIVE: Blood transfusion is frequently necessary following adult spinal deformity (ASD) surgery. We sought to develop predictive models for blood transfusion following ASD surgery, utilizing both classification tree and random forest machine-learning approaches. SUMMARY OF BACKGROUND DATA: Past models for transfusion risk among spine surgery patients are disadvantaged through use of single-institutional data, potentially limiting generalizability...
December 5, 2017: Spine
https://www.readbyqxmd.com/read/29188157/predicting-quality-of-life-changes-in-hemodialysis-patients-using-machine-learning-generation-of-an-early-warning-system
#2
Shoab Saadat, Ayesha Aziz, Hira Ahmad, Hira Imtiaz, Zara S Sohail, Alvina Kazmi, Sanaa Aslam, Naveen Naqvi, Sidra Saadat
Objective To predict changes in the quality of life scores of hemodialysis patients for the coming month and the development of an early warning system using machine learning Methods It was a prospective cohort study (one-month duration) at the dialysis center of a tertiary care hospital in Pakistan. The study started on 1st October 2016. About 78 patients have been enrolled till now. Bachelor of Medicine and Bachelor of Surgery (MBBS) qualified doctors administered a proforma with demographics and the validated Urdu version of World Health Organization Quality Of Life-BREF (WHOQOL-BREF)...
September 25, 2017: Curēus
https://www.readbyqxmd.com/read/29145893/normalization-of-the-microbiota-in-patients-after-treatment-for-colonic-lesions
#3
Marc A Sze, Nielson T Baxter, Mack T Ruffin, Mary A M Rogers, Patrick D Schloss
BACKGROUND: Colorectal cancer is a worldwide health problem. Despite growing evidence that members of the gut microbiota can drive tumorigenesis, little is known about what happens to it after treatment for an adenoma or carcinoma. This study tested the hypothesis that treatment for adenoma or carcinoma alters the abundance of bacterial populations associated with disease to those associated with a normal colon. We tested this hypothesis by sequencing the 16S rRNA genes in the feces of 67 individuals before and after treatment for adenoma (N = 22), advanced adenoma (N = 19), and carcinoma (N = 26)...
November 16, 2017: Microbiome
https://www.readbyqxmd.com/read/29134348/machine-learning-based-quantitative-texture-analysis-of-ct-images-of-small-renal-masses-differentiation-of-angiomyolipoma-without-visible-fat-from-renal-cell-carcinoma
#4
Zhichao Feng, Pengfei Rong, Peng Cao, Qingyu Zhou, Wenwei Zhu, Zhimin Yan, Qianyun Liu, Wei Wang
OBJECTIVE: To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). METHODS: This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images...
November 13, 2017: European Radiology
https://www.readbyqxmd.com/read/29132635/need-of-informatics-in-designing-interoperable-clinical-registries
#5
Majid Rastegar-Mojarad, Sunghwan Sohn, Liwei Wang, Feichen Shen, Troy C Bleeker, William A Cliby, Hongfang Liu
Clinical registries are designed to collect information relating to a particular condition for research or quality improvement. Intuitively, informatics in the area of data management and extraction plays a central role in clinical registries. Due to various reasons such as lack of informatics awareness or expertise, there may be little informatics involvement in designing clinical registries. In this paper, we studied a clinical registry from two critical perspectives, data quality and interoperability, where informatics can play a role...
December 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/29132626/early-hospital-mortality-prediction-of-intensive-care-unit-patients-using-an-ensemble-learning-approach
#6
Aya Awad, Mohamed Bader-El-Den, James McNicholas, Jim Briggs
BACKGROUND: Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By contrast, early mortality prediction for intensive care unit patients remains an open challenge. Most research has focused on severity of illness scoring systems or data mining (DM) models designed for risk estimation at least 24 or 48h after ICU admission...
December 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/29121286/prediction-of-persistent-post-surgery-pain-by-preoperative-cold-pain-sensitivity-biomarker-development-with-machine-learning-derived-analysis
#7
J Lötsch, A Ultsch, E Kalso
Background: To prevent persistent post-surgery pain, early identification of patients at high risk is a clinical need. Supervised machine-learning techniques were used to test how accurately the patients' performance in a preoperatively performed tonic cold pain test could predict persistent post-surgery pain. Methods: We analysed 763 patients from a cohort of 900 women who were treated for breast cancer, of whom 61 patients had developed signs of persistent pain during three yr of follow-up...
October 1, 2017: British Journal of Anaesthesia
https://www.readbyqxmd.com/read/29066360/early-detection-of-ureteropelvic-junction-obstruction-using-signal-analysis-and-machine-learning-a-dynamic-solution-to-a-dynamic-problem
#8
Emily S Blum, Antonio R Porras, Elijah Biggs, Pooneh R Tabrizi, Rachael D Sussman, Bruce M Sprague, Eglal Shalaby-Rana, Massoud Majd, Hans G Pohl, Marius George Linguraru
PURPOSE: To define features that describe the dynamic information in diuresis renograms (DR) for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction. MATERIALS AND METHODS: We studied the DR from 55 patients (age 80±70 days) with congenital hydronephrosis at initial presentation. Five patients had bilaterally affected kidneys, totaling 60 DR. Surgery was performed on 35 kidneys. We extracted 45 features (based on curve shape and wavelet analysis) from the drainage curves recorded after administration of furosemide...
October 21, 2017: Journal of Urology
https://www.readbyqxmd.com/read/29042101/machine-learning-phenotypic-classification-of-bicuspid-aortopathy
#9
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
#10
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
#11
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
#12
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...
November 2017: Epilepsia
https://www.readbyqxmd.com/read/28987701/comparison-of-perioperative-automated-versus-manual-two-dimensional-tumor-analysis-in-glioblastoma-patients
#13
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
#14
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
#15
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
#16
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
#17
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
#18
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
#19
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
#20
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
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