Results 1 to 10 of about 55,717 (192)

Systematic review of learning curves in robot-assisted surgery. [PDF]

BJS Open, 2020
A broad systematic literature review was performed to characterize the current evidence base and appraise the methods used to measure and define learning curves for surgeons performing robot‐assisted surgery, taking a holistic, panspecialty view. The learning curve estimates identified are subject to considerable uncertainty, and robust evidence was ...
Soomro NA, Hashimoto DA, Porteous AJ, Ridley CJA, Marsh WJ, Ditto R, Roy S.   +6 more
europepmc   +2 more sources

Integrating presence‐only and presence–absence data to model changes in species geographic ranges: An example in the Neotropics

Journal of Biogeography, Volume 50, Issue 9, Page 1561-1575, September 2023., 2023
Abstract Aim Anthropogenic changes such as land use and climate change affect species' geographic ranges, causing range shifts, contractions, or expansions. However, data on range dynamics are insufficient, heterogeneous, and spatially and temporally biased in most regions.
Florencia Grattarola, Diana E. Bowler, Petr Keil   +2 more
wiley   +1 more source

Climate change adaptation in Central America: A review of the national policy efforts

Latin American Policy, Volume 13, Issue 2, Page 276-327, November 2022., 2022
Abstract The latest comparative studies of climate policies reinforce the fundamental importance of employing adaptation planning alongside national development strategies. While these studies are necessary to document and share the knowledge of the practices and experiences undertaken at the national level, documents are still scarce on regions of ...
Luis D. Segura, Annemarie van Zeijl‐Rozema, Pim Martens   +2 more
wiley   +1 more source

Large‐scale, image‐based tree species mapping in a tropical forest using artificial perceptual learning

Methods in Ecology and Evolution, Volume 12, Issue 4, Page 608-618, April 2021., 2021
Abstract Information about the spatial distribution of species lies at the heart of many important questions in ecology. Logistical limitations and collection biases, however, limit the availability of such data at ecologically relevant scales. Remotely sensed information can alleviate some of these concerns, but presents challenges associated with ...
Chengliang Tang, María Uriarte, Helen Jin, Douglas C. Morton, Tian Zheng, Aaron Ellison   +5 more
wiley   +1 more source

Prostatectomía radical robótica: revisión de nuestra curva de aprendizaje [PDF]

Actas Urológicas Españolas, 2007
Objetivo: Presentamos los primeros casos de nuestra serie de prostatectomía radical robótica con Da Vinci (PRRdaV), que corresponden a la curva de aprendizaje (CA) del cirujano que se ha iniciado en la técnica. Métodos: Se revisan los 20 primeros pacientes sometidos a PRRdaV y realizados por un cirujano experto, sin entrenamiento laparoscópico previo ...
Villavicencio Mavrich, H., Esquena, S., Palou Redorta, J., Gómez Ruíz, J.J.   +3 more
openaire   +3 more sources

TaTME, tips para iniciar la curva de aprendizaje

Revista Argentina de Coloproctología, 2021
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Adrián Mattacheo, Joaquín Tognelli, Julio Lococo   +2 more
openaire   +2 more sources

Shortening surgical training through robotics: randomized clinical trial of laparoscopic versus robotic surgical learning curves

BJS Open, Volume 4, Issue 6, Page 1100-1108, December 2020., 2020
Medical students and surgical trainees were randomized to robotic or laparoscopic simulator training followed by cadaveric surgical tasks. The robotic groups had a shorter learning curve with better task performance. Another advantage for robotic surgery Background Minimally invasive surgery is the standard technique for many operations.
T. M. H. Gall, W. Alrawashdeh, N. Soomro, S. White, L. R. Jiao   +4 more
wiley   +1 more source

Locoregional recurrences after transanal total mesorectal excision of rectal cancer during implementation

BJS (British Journal of Surgery), Volume 107, Issue 9, Page 1211-1220, August 2020., 2020
During the learning curve, the transanal total mesorectal excision procedure is associated with a high multifocal local recurrence rate, which appears to be related to suboptimal execution rather than the technique, and necessitates prolonged proctoring, optimization of the technique avoiding spillage, participation in controlled clinical trials with ...
S. E. van Oostendorp, H. J. Belgers, B. T. Bootsma, J. C. Hol, E. J. T. H. Belt, W. Bleeker, F. C. Den Boer, A. Demirkiran, M. S. Dunker, H. F. J. Fabry, E. J. R. Graaf, J. J. Knol, S. J. Oosterling, G. D. Slooter, D. J. A. Sonneveld, A. K. Talsma, H. L. Van Westreenen, M. Kusters, R. Hompes, H. J. Bonjer, C. Sietses, J. B. Tuynman   +21 more
wiley   +1 more source

Colangiografía intraoperatoria: curva de aprendizaje en una Residencia de Cirugía General

Revista Argentina de Cirugía, 2020
Background: The use of dynamic intra-operative cholangiography (dIOC) during laparoscopic cholecystectomy (Lap Chole) remains a topic under discussion. Objectives: This study aims to describe and evaluate the learning curve and findings in the dIOC during laparoscopic cholecystectomies performed by Residents of General Surgery, including it as a tool ...
Santiago Darrigran, Lucas A. Ituriza, Nicolás Lanza, Luciano Mercuri, Federico Aispuro, Agustín Chichizola, Jorge López Camelo, Nicolàs Guerrini, Carlos M. Canullán   +8 more
openaire   +3 more sources

Machine learning to predict early recurrence after oesophageal cancer surgery

BJS (British Journal of Surgery), Volume 107, Issue 8, Page 1042-1052, July 2020., 2020
Early recurrence after surgery for adenocarcinoma of the oesophagus is common. A risk prediction model was derived using modern machine learning methods that accurately predicts risk of early recurrence using postoperative pathology. Machine learning may help Background Early cancer recurrence after oesophagectomy is a common problem, with an incidence
S. A. Rahman, R. C. Walker, M. A. Lloyd, B. L. Grace, G. I. van Boxel, B. F. Kingma, J. P. Ruurda, R. van Hillegersberg, S. Harris, S. Parsons, S. Mercer, E. A. Griffiths, J. R. O'Neill, R. Turkington, R. C. Fitzgerald, T. J. Underwood, the OCCAMS Consortium, Ayesha Noorani, Rachael Fels Elliott, Paul A.W. Edwards, Nicola Grehan, Barbara Nutzinger, Jason Crawte, Hamza Chettouh, Gianmarco Contino, Xiaodun Li, Eleanor Gregson, Sebastian Zeki, Rachel de la Rue, Shalini Malhotra, Simon Tavaré, Andy G. Lynch, Mike L. Smith, Jim Davies, Charles Crichton, Nick Carroll, Peter Safranek, Andrew Hindmarsh, Vijayendran Sujendran, Stephen J. Hayes, Yeng Ang, Shaun R. Preston, Sarah Oakes, Izhar Bagwan, Vicki Save, Richard J.E. Skipworth, Ted R. Hupp, J. Robert O'Neill, Olga Tucker, Andrew Beggs, Philippe Taniere, Sonia Puig, Timothy J. Underwood, Fergus Noble, James P. Byrne, Jamie J. Kelly, Jack Owsley, Hugh Barr, Neil Shepherd, Oliver Old, Jesper Lagergren, James Gossage, Andrew Davies Fuju Chang, Janine Zylstra, Vicky Goh, Francesca D. Ciccarelli, Grant Sanders, Richard Berrisford, Catherine Harden, David Bunting, Mike Lewis, Ed Cheong, Bhaskar Kumar, Simon L. Parsons, Irshad Soomro, Philip Kaye, John Saunders, Laurence Lovat, Rehan Haidry, Victor Eneh, Laszlo Igali, Michael Scott, Shamila Sothi, Sari Suortamo, Suzy Lishman, George B. Hanna, Christopher J. Peters, Anna Grabowska   +87 more
wiley   +1 more source