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https://www.readbyqxmd.com/read/29448809/utilizing-machine-learning-and-automated-performance-metrics-to-evaluate-robot-assisted-radical-prostatectomy-performance-and-predict-outcomes
#1
Andrew Hung, Jian Chen, Zhengping Che, Tanachat Nilanon, Anthony Jarc, Micha Titus, Paul Oh, Inderbir Singh Gill, Yan Liu
Purpose Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). Methods We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2days) from 78 RARP cases, and selected the algorithm with the best performance...
February 16, 2018: Journal of Endourology
https://www.readbyqxmd.com/read/29427011/self-learning-computers-for-surgical-planning-and-prediction-of-postoperative-alignment
#2
Renaud Lafage, Sébastien Pesenti, Virginie Lafage, Frank J Schwab
PURPOSE: In past decades, the role of sagittal alignment has been widely demonstrated in the setting of spinal conditions. As several parameters can be affected, identifying the driver of the deformity is the cornerstone of a successful treatment approach. Despite the importance of restoring sagittal alignment for optimizing outcome, this task remains challenging. Self-learning computers and optimized algorithms are of great interest in spine surgery as in that they facilitate better planning and prediction of postoperative alignment...
February 9, 2018: European Spine Journal
https://www.readbyqxmd.com/read/29412496/characterization-of-active-and-infiltrative-tumorous-subregions-from-normal-tissue-in-brain-gliomas-using-multiparametric-mri
#3
Anahita Fathi Kazerooni, Mahnaz Nabil, Mehdi Zeinali Zadeh, Kavous Firouznia, Farid Azmoudeh-Ardalan, Alejandro F Frangi, Christos Davatzikos, Hamidreza Saligheh Rad
BACKGROUND: Targeted localized biopsies and treatments for diffuse gliomas rely on accurate identification of tissue subregions, for which current MRI techniques lack specificity. PURPOSE: To explore the complementary and competitive roles of a variety of conventional and quantitative MRI methods for distinguishing subregions of brain gliomas. STUDY TYPE: Prospective. POPULATION: Fifty-one tissue specimens were collected using image-guided localized biopsy surgery from 10 patients with newly diagnosed gliomas...
February 7, 2018: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/29389679/artificial-intelligence-in-surgery-promises-and-perils
#4
Daniel A Hashimoto, Guy Rosman, Daniela Rus, Ozanan R Meireles
OBJECTIVE: The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments. SUMMARY BACKGROUND DATA: AI is composed of various subfields that each provide potential solutions to clinical problems. Each of the core subfields of AI reviewed in this piece has also been used in other industries such as the autonomous car, social networks, and deep learning computers...
January 31, 2018: Annals of Surgery
https://www.readbyqxmd.com/read/29370004/plastic-surgeon-led-ultrasound
#5
Georgette Oni, Whitney Chow, Venkat Ramakrishnan, Matthew Griffiths
BACKGROUND: Portable high-frequency ultrasound is a useful adjunct to a plastic surgeon's practice. With a short learning curve, this patient-friendly imaging modality has a variety of uses that aid patient management/treatment plans. The authors describe clinical cases and review the literature regarding ultrasound performed by the surgeon. METHODS: The Sonosite S-Nerve machine with the L25X transducer was used (depth, 4.3 cm). Clinical cases that ordinarily would have been referred to the radiology department were taken from the day-to-day practice of the senior author (M...
February 2018: Plastic and Reconstructive Surgery
https://www.readbyqxmd.com/read/29339512/neural-preservation-underlies-speech-improvement-from-auditory-deprivation-in-young-cochlear-implant-recipients
#6
Gangyi Feng, Erin M Ingvalson, Tina M Grieco-Calub, Megan Y Roberts, Maura E Ryan, Patrick Birmingham, Delilah Burrowes, Nancy M Young, Patrick C M Wong
Although cochlear implantation enables some children to attain age-appropriate speech and language development, communicative delays persist in others, and outcomes are quite variable and difficult to predict, even for children implanted early in life. To understand the neurobiological basis of this variability, we used presurgical neural morphological data obtained from MRI of individual pediatric cochlear implant (CI) candidates implanted younger than 3.5 years to predict variability of their speech-perception improvement after surgery...
January 16, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29315279/a-regression-model-for-predicting-shape-deformation-after-breast-conserving-surgery
#7
Hooshiar Zolfagharnasab, Sílvia Bessa, Sara P Oliveira, Pedro Faria, João F Teixeira, Jaime S Cardoso, Hélder P Oliveira
Breast cancer treatments can have a negative impact on breast aesthetics, in case when surgery is intended to intersect tumor. For many years mastectomy was the only surgical option, but more recently breast conserving surgery (BCS) has been promoted as a liable alternative to treat cancer while preserving most part of the breast. However, there is still a significant number of BCS intervened patients who are unpleasant with the result of the treatment, which leads to self-image issues and emotional overloads...
January 9, 2018: Sensors
https://www.readbyqxmd.com/read/29305324/real-world-outcomes-in-patients-with-neovascular-age-related-macular-degeneration-treated-with-intravitreal-vascular-endothelial-growth-factor-inhibitors
#8
REVIEW
Hemal Mehta, Adnan Tufail, Vincent Daien, Aaron Lee, Vuong Nguyen, Mehmet Ozturk, Daniel Barthelmes, Mark C Gillies
Clinical trials identified intravitreal vascular endothelial growth factor inhibitors (anti-VEGF agents) have the potential to stabilise or even improve visual acuity outcomes in neovascular age-related macular degeneration (AMD), a sight-threatening disease. Real-world evidence allows us to assess whether results from randomised controlled trials can be applied to the general population. We describe the development of global registries, in particular the Fight Retinal Blindness! registry that originated in Australia, the United Kingdom AMD Electronic Medical Records User Group and the IRIS registry in the USA...
January 2, 2018: Progress in Retinal and Eye Research
https://www.readbyqxmd.com/read/29229144/postoperative-neonatal-mortality-prediction-using-superlearning
#9
Jennifer N Cooper, Peter C Minneci, Katherine J Deans
BACKGROUND: The variable risks associated with neonatal surgery present a challenge to accurate mortality prediction. We aimed to apply superlearning, an ensemble machine learning method, to the prediction of 30-day neonatal postoperative mortality. MATERIALS AND METHODS: We included neonates in the 2012-2014 National Surgical Quality Improvement Program Pediatric. Patients treated in 2012-13 were used in model development (n = 6499), and patients treated in 2014 formed the validation sample (n = 3552)...
January 2018: Journal of Surgical Research
https://www.readbyqxmd.com/read/29215501/predictive-modeling-for-blood-transfusion-following-adult-spinal-deformity-surgery-a-tree-based-machine-learning-approach
#10
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
#11
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
#12
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
#13
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
#14
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
#15
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
#16
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
#17
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: We sought to define features that describe the dynamic information in diuresis renograms for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction. MATERIALS AND METHODS: We studied the diuresis renogram of 55 patients with a mean ± age of 80 ± 70 days who had congenital hydronephrosis at initial presentation. Five patients had bilaterally affected kidneys for a total of 60 diuresis renograms. Surgery was performed on 35 kidneys...
October 21, 2017: Journal of Urology
https://www.readbyqxmd.com/read/29042101/machine-learning-phenotypic-classification-of-bicuspid-aortopathy
#18
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
#19
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
#20
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
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