Read by QxMD icon Read

Machine learning surgery

Jeremy Brown, Conor O'Brien, Sarah Leung, Kristoffel Dumon, David Lee, Katherine Kuchenbecker
OBJECTIVE: Most trainees begin learning robotic minimally invasive surgery by performing inanimate practice tasks with clinical robots such as the Intuitive Surgical da Vinci. Expert surgeons are commonly asked to evaluate these performances using standardized five-point rating scales, but doing such ratings is time consuming, tedious, and somewhat subjective. This article presents an automatic skill evaluation system that analyzes only the contact force with the task materials, the broad-bandwidth accelerations of the robotic instruments and camera, and the task completion time...
December 2, 2016: IEEE Transactions on Bio-medical Engineering
Seunghoon Lee, Seong-Wook Seo, Juyoung Hwang, Ho Jun Seol, Do-Hyun Nam, Jung-Il Lee, Doo-Sik Kong
Communicating hydrocephalus (HCP) in vestibular schwannomas (VS) after gamma knife radiosurgery (GKRS) has been reported in the literature. However, little information about its incidence and risk factors after GKRS for intracranial schwannomas is yet available. The objective of this study was to identify the incidence and risk factors for developing communicating HCP after GKRS for intracranial schwannomas. We retrospectively reviewed a total of 702 patients with intracranial schwannomas who were treated with GKRS between January 2002 and December 2015...
November 23, 2016: Cancer Medicine
Ali Wadal, Tusneem Ahmed Elhassan, Hajer Ahmed Zein, Manar Elsheikh Abdel-Rahman, Ahmed Hassan Fahal
Post-operative recurrence in mycetoma after adequate medical and surgical treatment is common and a serious problem. It has health, socio-economic and psychological detrimental effects on patients and families. It is with this in mind, we set out to determine the predictors of post-operative recurrence in mycetoma. The study included 1013 patients with Madurella mycetomatis causing eumycetoma who underwent surgical excision at the Mycetoma Research Centre, Khartoum, Sudan in the period 1991-2015. The clinical records of these patients were reviewed and relevant information was collected using a pre-designed data collection sheet...
October 2016: PLoS Neglected Tropical Diseases
E Tan, F Lin, L Sheck, P Salmon, S Ng
PURPOSE: To derive a decision rule for predicting surgical complexity in periorbital basal cell carcinoma (pBCC). DESIGN: Prospective, cohort study. PARTICIPANTS: Patients referred to an oculoplastic service for excision of pBCC from September 2010 to November 2015 METHODS: This study was conducted at two centres in New Zealand from September 2010 to November 2015. Baseline demographic information, and an initial assessment of operative complexity (a four-point grading scale) were collected...
October 14, 2016: Journal of the European Academy of Dermatology and Venereology: JEADV
Marcel Ivanov, Alexandru Budu, Hugh Sims-Williams, Ion Poeata
BACKGROUND: Our aim was to evaluate the utility of modern intraoperative ultrasound in the resection of a wide variety of spinal intradural pathological entities. MATERIALS AND METHODS: The authors evaluated patients with spinal cord pathology treated between January 2006 and September 2015. Intraoperative standard B-mode images were acquired using a 3.5-12 MHz US probes (linear and curvilinear) on various ultrasound machines. The benefits and disadvantages of intraoperative ultrasound (iUS) were assessed for each case...
October 3, 2016: World Neurosurgery
Dan Valsky, Odeya Marmor-Levin, Marc Deffains, Renana Eitan, Kim T Blackwell, Hagai Bergman, Zvi Israel
BACKGROUND: Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the STN borders is performed manually by a neurophysiologist. The exact detection of the borders is difficult, especially detecting the transition between the STN and the substantia nigra pars reticulata. Consequently, demarcation may be inaccurate, leading to suboptimal location of the DBS lead and inadequate clinical outcomes...
October 6, 2016: Movement Disorders: Official Journal of the Movement Disorder Society
Hamed Asadi, Hong Kuan Kok, Seamus Looby, Paul Brennan, Alan O'Hare, John Thornton
PURPOSE: This study aims to identify factors influencing outcome in brain arteriovenous malformations (BAVM) treated with endovascular embolisation. We also assessed the feasibility of using machine learning techniques to prognosticate and predict outcome and compared this to conventional statistical analyses. METHODS: A retrospective study of patients undergoing endovascular treatment of BAVM over a 22-year period in a national neuroscience centre was performed...
September 28, 2016: World Neurosurgery
Wenjun Xu, Jie Chen, Henry Y K Lau, Hongliang Ren
BACKGROUND: Accurate motion control of flexible surgical manipulators is crucial in tissue manipulation tasks. The tendon-driven serpentine manipulator (TSM) is one of the most widely adopted flexible mechanisms in minimally invasive surgery because of its enhanced maneuverability in torturous environments. TSM, however, exhibits high nonlinearities and conventional analytical kinematics model is insufficient to achieve high accuracy. METHODS: To account for the system nonlinearities, we applied a data driven approach to encode the system inverse kinematics...
September 20, 2016: International Journal of Medical Robotics + Computer Assisted Surgery: MRCAS
Ligang Luo, Liping Li, Jiajia Hu, Xiaozhe Wang, Boulin Hou, Tianze Zhang, Lue Ping Zhao
BACKGROUND: Healthcare providers generate a huge amount of biomedical data stored in either legacy system (paper-based) format or electronic medical records (EMR) around the world, which are collectively referred to as big biomedical data (BBD). To realize the promise of BBD for clinical use and research, it is an essential step to extract key data elements from unstructured medical records into patient-centered electronic health records with computable data elements. Our objective is to introduce a novel solution, known as a double-reading/entry system (DRESS), for extracting clinical data from unstructured medical records (MR) and creating a semi-structured electronic health record database, as well as to demonstrate its reproducibility empirically...
2016: BMC Medical Informatics and Decision Making
M Gram, J Erlenwein, F Petzke, D Falla, M Przemeck, M I Emons, M Reuster, S S Olesen, A M Drewes
BACKGROUND: Opioids are often used for pain treatment, but the response is often insufficient and dependent on e.g. the pain condition, genetic factors and drug class. Thus, there is an urgent need to identify biomarkers to enable selection of the appropriate drug for the individual patient, a concept known as personalized medicine. Quantitative sensory testing (QST) and clinical parameters can provide some guidance for response, but better and more objective biomarkers are urgently warranted...
July 29, 2016: European Journal of Pain: EJP
Ana Monsalve-Torra, Daniel Ruiz-Fernandez, Oscar Marin-Alonso, Antonio Soriano-Payá, Jaime Camacho-Mackenzie, Marisol Carreño-Jaimes
An abdominal aortic aneurysm is an abnormal dilatation of the aortic vessel at abdominal level. This disease presents high rate of mortality and complications causing a decrease in the quality of life and increasing the cost of treatment. To estimate the mortality risk of patients undergoing surgery is complex due to the variables associated. The use of clinical decision support systems based on machine learning could help medical staff to improve the results of surgery and get a better understanding of the disease...
August 2016: Journal of Biomedical Informatics
Olivier Sobrie, Mohammed El Amine Lazouni, Saïd Mahmoudi, Vincent Mousseau, Marc Pirlot
BACKGROUND AND OBJECTIVE: The principal challenges in the field of anesthesia and intensive care consist of reducing both anesthetic risks and mortality rate. The ASA score plays an important role in patients' preanesthetic evaluation. In this paper, we propose a methodology to derive simple rules which classify patients in a category of the ASA scale on the basis of their medical characteristics. METHODS: This diagnosis system is based on MR-Sort, a multiple criteria decision analysis model...
September 2016: Computer Methods and Programs in Biomedicine
Manfredo Atzori, Arjan Gijsberts, Claudio Castellini, Barbara Caputo, Anne-Gabrielle Mittaz Hager, Simone Elsig, Giorgio Giatsidis, Franco Bassetto, Henning Müller
Improving the functionality of prosthetic hands with noninvasive techniques is still a challenge. Surface electromyography (sEMG) currently gives limited control capabilities; however, the application of machine learning to the analysis of sEMG signals is promising and has recently been applied in practice, but many questions still remain. In this study, we recorded the sEMG activity of the forearm of 11 male subjects with transradial amputation who were mentally performing 40 hand and wrist movements. The classification performance and the number of independent movements (defined as the subset of movements that could be distinguished with >90% accuracy) were studied in relationship to clinical parameters related to the amputation...
2016: Journal of Rehabilitation Research and Development
Kevin Bretonnel Cohen, Benjamin Glass, Hansel M Greiner, Katherine Holland-Bouley, Shannon Standridge, Ravindra Arya, Robert Faist, Diego Morita, Francesco Mangano, Brian Connolly, Tracy Glauser, John Pestian
We describe the development and evaluation of a system that uses machine learning and natural language processing techniques to identify potential candidates for surgical intervention for drug-resistant pediatric epilepsy. The data are comprised of free-text clinical notes extracted from the electronic health record (EHR). Both known clinical outcomes from the EHR and manual chart annotations provide gold standards for the patient's status. The following hypotheses are then tested: 1) machine learning methods can identify epilepsy surgery candidates as well as physicians do and 2) machine learning methods can identify candidates earlier than physicians do...
2016: Biomedical Informatics Insights
Hsin-Yun Wu, Cihun-Siyong Alex Gong, Shih-Pin Lin, Kuang-Yi Chang, Mei-Yung Tsou, Chien-Kun Ting
Patient-controlled epidural analgesia (PCEA) has been applied to reduce postoperative pain in orthopedic surgical patients. Unfortunately, PCEA is occasionally accompanied by nausea and vomiting. The logistic regression (LR) model is widely used to predict vomiting, and recently support vector machines (SVM), a supervised machine learning method, has been used for classification and prediction. Unlike our previous work which compared Artificial Neural Networks (ANNs) with LR, this study uses a SVM-based predictive model to identify patients with high risk of vomiting during PCEA and comparing results with those derived from the LR-based model...
2016: Scientific Reports
Paul Thottakkara, Tezcan Ozrazgat-Baslanti, Bradley B Hupf, Parisa Rashidi, Panos Pardalos, Petar Momcilovic, Azra Bihorac
OBJECTIVE: To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN: Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. PATIENTS: 50,318 adult patients undergoing major surgery. MEASUREMENTS: We evaluated the performance of logistic regression, generalized additive models, naïve Bayes and support vector machines for forecasting postoperative sepsis and acute kidney injury...
2016: PloS One
Hideo Chihara, Naoya Oishi, Akira Ishii, Toshihiro Munemitsu, Daisuke Arai, Hiroyuki Ikeda, Susumu Miyamoto
BACKGROUND AND AIMS: Detecting detailed atherosclerotic plaques is important to reduce risk factors during surgery. However, there are few methods to evaluate them during surgery. The aim of this study was to establish an in vivo, non-contact, and label-free imaging method for identifying atherosclerotic plaque lesions from outside vessels with a diffuse-reflectance near-infrared (NIR) hyperspectral imaging (HSI) system. METHODS: NIR spectra between 1000 and 2350 nm were measured using an NIR HSI imaging system outside the exposed abdominal aorta in five Watanabe Heritable Hyperlipidemic (WHHL) rabbits in vivo...
July 2016: Atherosclerosis
Woojae Kim, Ku Sang Kim, Rae Woong Park
OBJECTIVES: Breast cancer has a high rate of recurrence, resulting in the need for aggressive treatment and close follow-up. However, previously established classification guidelines, based on expert panels or regression models, are controversial. Prediction models based on machine learning show excellent performance, but they are not widely used because they cannot explain their decisions and cannot be presented on paper in the way that knowledge is customarily represented in the clinical world...
April 2016: Healthcare Informatics Research
Patrick C Sanger, Gabrielle H van Ramshorst, Ezgi Mercan, Shuai Huang, Andrea L Hartzler, Cheryl A L Armstrong, Ross J Lordon, William B Lober, Heather L Evans
BACKGROUND: Surgical site infection (SSI) remains a common, costly, and morbid health care-associated infection. Early detection can improve outcomes, yet previous risk models consider only baseline risk factors (BF) not incorporating a proximate and timely data source-the wound itself. We hypothesize that incorporation of daily wound assessment improves the accuracy of SSI identification compared with traditional BF alone. STUDY DESIGN: A prospective cohort of 1,000 post open abdominal surgery patients at an academic teaching hospital were examined daily for serial features (SF), for example, wound characteristics and vital signs, in addition to standard BF, for example, wound class...
August 2016: Journal of the American College of Surgeons
David Whiteside, Douglas N Martini, Adam S Lepley, Ronald F Zernicke, Grant C Goulet
BACKGROUND: Ulnar collateral ligament (UCL) reconstruction surgeries in Major League Baseball (MLB) have increased significantly in recent decades. Although several risk factors have been proposed, a scientific consensus is yet to be reached, providing challenges to those tasked with preventing UCL injuries. PURPOSE: To identify significant predictors of UCL reconstruction in MLB pitchers. STUDY DESIGN: Case control study; Level of evidence, 3...
September 2016: American Journal of Sports Medicine
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"