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Video-based learning

Byunghyun Kim, Soojin Cho
At present, a number of computer vision-based crack detection techniques have been developed to efficiently inspect and manage a large number of structures. However, these techniques have not replaced visual inspection, as they have been developed under near-ideal conditions and not in an on-site environment. This article proposes an automated detection technique for crack morphology on concrete surface under an on-site environment based on convolutional neural networks (CNNs). A well-known CNN, AlexNet is trained for crack detection with images scraped from the Internet...
October 14, 2018: Sensors
Manuel Castillo-Angeles, Rodrigo Calvillo-Ortiz, Danilo Acosta, Ammara A Watkins, Amy Evenson, Katharyn M Atkins, Tara S Kent
OBJECTIVE: Trainee mistreatment, either intentional or unintentional, negatively affects the learning environment. This study was undertaken to evaluate the impact of an educational intervention about mistreatment and the learning environment on general surgery residents. DESIGN: Video-based modules were developed and added to the residency curriculum. Modules provided definitions and examples of active and passive mistreatment and components of positive and negative learning environments...
October 11, 2018: Journal of Surgical Education
Liping Xie, Dacheng Tao, Haikun Wei
Video-based facial expression recognition has received substantial attention over the past decade, while early expression detection (EED) is still a relatively new and challenging problem. The goal of EED is to identify an expression as quickly as possible after the expression starts and before it ends. This timely ability has many potential applications, ranging from human-computer interaction to security. The max-margin early event detector (MMED) is a well-known ranking model for early event detection. It can achieve competitive EED performance but suffers from several critical limitations: 1) MMED lacks flexibility in extracting useful information for segment comparison, which leads to poor performance in exploring the ranking relation between segment pairs; 2) the training process is slow due to the large number of constraints, and the memory requirement is also usually hard to satisfy; and 3) MMED is linear in nature, and hence may not be appropriate for data in a nonlinear feature space...
October 3, 2018: IEEE Transactions on Neural Networks and Learning Systems
Yang Kun, Jacques Hubert, Luo Bin, Wang Xing Huan
OBJECTIVE: Video-based teaching is considered highly effective in debriefing, especially in minimally invasive surgeries. In this study, the benefits of using a new integrated video recording system, were investigated and compared to those of the standard basic skills robotic training procedure. DESIGN: Fifty residents from the 2nd and 3rd year medical faculty without any experience of robot usage or laparoscopy were randomized into 2 groups: group A--a natural self-training group without a trainer, and group B--a self-training group assisted by an integrated video recording system during training...
October 3, 2018: Journal of Surgical Education
Marcelo Niglio de Figueiredo, Lorena Krippeit, Gabriele Ihorst, Heribert Sattel, Carma L Bylund, Andreas Joos, Jürgen Bengel, Claas Lahmann, Kurt Fritzsche, Alexander Wuensch
OBJECTIVE: To investigate the effect of the number of coaching sessions after communication skills training on the medical communicative performance of oncologists in clinical practice. METHODS/DESIGN: The training, consisting of a workshop and one (control group) vs. four (intervention group) sessions of individual coaching, was evaluated in a randomized controlled trial. Eligible participants included physicians working in any setting where patients with oncological diseases were treated...
2018: PloS One
Sophie Lohmann, Benjamin X White, Zhen Zuo, Man-Pui Sally Chan, Alex Morales, Bo Li, Chengxiang Zhai, Dolores Albarracín
OBJECTIVES: Social media messages have been increasingly used in health campaigns about prevention, testing, and treatment of HIV. We identified factors leading to the retransmission of messages from expert social media accounts to create data-driven recommendations for online HIV messaging. DESIGN AND METHODS: We sampled 20,201 HIV-related tweets (posted between 2010 and 2017) from 37 HIV experts. Potential predictors of retransmission were identified based on prior literature and machine learning methods and were subsequently analyzed using multilevel negative binomial models...
October 4, 2018: AIDS
Travis J Saunders, Dany J MacDonald, Jennifer L Copeland, Patricia E Longmuir, Joel D Barnes, Kevin Belanger, Brenda Bruner, Melanie J Gregg, Nathan Hall, Angela M Kolen, Barbi Law, Luc J Martin, Dwayne Sheehan, Michelle R Stone, Sarah J Woodruff, Mark S Tremblay
BACKGROUND: Physical literacy is the foundation of a physically active lifestyle. Sedentary behaviour displays deleterious associations with important health indicators in children. However, the association between sedentary behaviour and physical literacy is unknown. The purpose of this study was to identify the aspects of physical literacy that are associated with key modes of sedentary behaviour among Canadian children participating in the RBC-CAPL Learn to Play study. METHODS: A total of 8,307 children aged 8...
October 2, 2018: BMC Public Health
Marc-Andre Carbonneau, Eric Granger, Ghyslain Gagnon
A growing number of applications, e.g., video surveillance and medical image analysis, require training recognition systems from large amounts of weakly annotated data, while some targeted interactions with a domain expert are allowed to improve the training process. In such cases, active learning (AL) can reduce labeling costs for training a classifier by querying the expert to provide the labels of most informative instances. This paper focuses on AL methods for instance classification problems in multiple instance learning (MIL), where data are arranged into sets, called bags, which are weakly labeled...
October 1, 2018: IEEE Transactions on Neural Networks and Learning Systems
Yun Gu, Khushi Vyas, Jie Yang, Guang-Zhong Yang
Probe-based confocal laser endomicroscopy (pCLE) is an emerging tool for epithelial cancer diagnosis, which enables in-vivo microscopic imaging during endoscopic procedures and facilitates the development of automatic recognition algorithms to identify the status of tissues. In this paper, we propose a transfer recurrent feature learning (TRFL) framework for classification tasks on pCLE videos. At the first stage, the discriminative feature of single pCLE frame is learned via generative adversarial networks based on both pCLE and histology modalities...
September 27, 2018: IEEE Transactions on Medical Imaging
Mengmi Zhang, Keng Teck Ma, Joohwee Lim, Qi Zhao, Jiashi Feng
We introduce a new problem of gaze anticipation on future frames which extends the conventional gaze prediction problem to go beyond current frames. To solve this problem, we propose a new generative adversarial network based model, Deep Future Gaze (DFG), encompassing two pathways: DFG-P is to anticipate gaze prior maps conditioned on the input frame which provides task influences; DFG-G is to learn to model both semantic and motion information in future frame generation. DFG-P and DFG-G are then fused to anticipate future gazes...
September 24, 2018: IEEE Transactions on Pattern Analysis and Machine Intelligence
Federico Nicolosi, Zefferino Rossini, Ismail Zaed, Angelos G Kolias, Maurizio Fornari, Franco Servadei
OBJECTIVE: Neurosurgical training is usually based on traditional sources of education, such as papers, books, direct surgical experience, and cadaveric hands-on courses. In low-middle income countries, standard education programs are often unavailable, mainly owing to the lack of human and economic resources. Introducing digital platforms in these settings could be an alternative solution for bridging the gap between Western and poor countries in neurosurgical knowledge. METHODS: The authors identified from the Internet the main digital platforms that could easily be adopted in low-middle income countries...
October 2018: Neurosurgical Focus
Aparna Sarangapani, Andrea N Simpson, John Snelgrove, Mary Higgins, Rory Windrim, Abheha Satkunaratnam
OBJECTIVE: Worldwide, the rate of operative vaginal deliveries has decreased, and as a result trainees are lacking exposure and training. The aim of this study was to determine whether a video-based masterclass can improve trainees' confidence, comfort, and knowledge in performing second stage labour assessments and selecting appropriate patients and instruments for operative vaginal deliveries. METHODS: Current University of Toronto obstetrics and gynaecology residents were invited to participate...
September 2018: Journal of Obstetrics and Gynaecology Canada: JOGC, Journal D'obstétrique et Gynécologie du Canada: JOGC
Kim A Bjorklund, Nicole Sommer, Michael W Neumeister, Steven J Kasten
OBJECTIVE: The aim of this study was to describe an operative performance rating system for plastic surgery residents and provide validity evidence for the instrument. METHODS: Three plastic surgery residents (PGY levels 1, 5, and 6) from Southern Illinois University School of Medicine (SIUSOM) performed a carpal tunnel release with audio video recording. The 3 videos were reviewed by 8 expert hand surgeons and 3 SIUSOM faculty using the operative performance rating system instrument to assess resident operative performance...
September 22, 2018: Journal of Surgical Education
Sanni Pöysä, Kati Vasalampi, Joona Muotka, Marja-Kristiina Lerkkanen, Anna-Maija Poikkeus, Jari-Erik Nurmi
BACKGROUND: Prior research has shown that engagement plays a significant role in students' academic learning. AIMS: The present study sought to expand the current understanding of students' engagement by examining how situational engagement during a particular lesson is associated with the observed teacher-student classroom interactions (i.e., emotional support, instructional support, and classroom organization) in the same lesson. SAMPLE: The participants were 709 Grade 7 students (47...
September 3, 2018: British Journal of Educational Psychology
Christine A Kauffman, Megan Derazin, Abdo Asmar, Jonathan D Kibble
Studies completed with undergraduate populations have shown that attendance positively correlates with academic performance. A marked decline in classroom attendance within medical school has recently been noticed with the availability of video capture of lectures and other online material. This study compares these in the era of online material. It took place during the second-year Gastrointestinal and Renal Systems module. Attendance was mandatory at team-based learning and case-based learning sessions on new material and voluntary at lectures (29 sessions) and case-based learning on material previously covered (9 sessions)...
December 1, 2018: Advances in Physiology Education
Michael D Vasilakakis, Dimitris K Iakovidis, Evaggelos Spyrou, Anastasios Koulaouzidis
Wireless Capsule Endoscopy (WCE) is a noninvasive diagnostic technique enabling the inspection of the whole gastrointestinal (GI) tract by capturing and wirelessly transmitting thousands of color images. Proprietary software "stitches" the images into videos for examination by accredited readers. However, the videos produced are of large length and consequently the reading task becomes harder and more prone to human errors. Automating the WCE reading process could contribute in both the reduction of the examination time and the improvement of its diagnostic accuracy...
2018: Computational and Mathematical Methods in Medicine
Maria Chiara Scali, Quirino Ciampi, Eugenio Picano, Eduardo Bossone, Francesco Ferrara, Rodolfo Citro, Paolo Colonna, Marco Fabio Costantino, Lauro Cortigiani, Antonello D' Andrea, Sergio Severino, Claudio Dodi, Nicola Gaibazzi, Maurizio Galderisi, Andrea Barbieri, Ines Monte, Fabio Mori, Barbara Reisenhofer, Federica Re, Fausto Rigo, Paolo Trambaiolo, Miguel Amor, Jorge Lowenstein, Pablo Martin Merlo, Clarissa Borguezan Daros, José Luis de Castro E Silva Pretto, Marcelo Haertel Miglioranza, Marco A R Torres, Clarissa Carmona de Azevedo Bellagamba, Daniel Quesada Chaves, Iana Simova, Albert Varga, Jelena Čelutkienė, Jaroslaw D Kasprzak, Karina Wierzbowska-Drabik, Piotr Lipiec, Paulina Weiner-Mik, Eva Szymczyk, Katarzyna Wdowiak-Okrojek, Ana Djordjevic-Dikic, Milica Dekleva, Ivan Stankovic, Aleksandar N Neskovic, Angela Zagatina, Giovanni Di Salvo, Julio E Perez, Ana Cristina Camarozano, Anca Irina Corciu, Alla Boshchenko, Fabio Lattanzi, Carlos Cotrim, Paula Fazendas, Maciej Haberka, Bozena Sobkowic, Wojciech Kosmala, Tomasz Witkowski, Piotr Gosciniak, Alessandro Salustri, Hugo Rodriguez-Zanella, Luis Ignacio Martin Leal, Alexandra Nikolic, Suzana Gligorova, Madalina-Loredana Urluescu, Maria Fiorino, Giuseppina Novo, Tamara Preradovic-Kovacevic, Miodrag Ostojic, Branko Beleslin, Bruno Villari, Michele De Nes, Marco Paterni, Clara Carpeggiani
BACKGROUND: The effectiveness trial "Stress echo (SE) 2020" evaluates novel applications of SE in and beyond coronary artery disease. The core protocol also includes 4-site simplified scan of B-lines by lung ultrasound, useful to assess pulmonary congestion. PURPOSE: To provide web-based upstream quality control and harmonization of B-lines reading criteria. METHODS: 60 readers (all previously accredited for regional wall motion, 53 B-lines naive) from 52 centers of 16 countries of SE 2020 network read a set of 20 lung ultrasound video-clips selected by the Pisa lab serving as reference standard, after taking an obligatory web-based learning 2-h module ( http://se2020...
September 25, 2018: Cardiovascular Ultrasound
Muhammad Hassan Khan, Manuel Schneider, Muhammad Shahid Farid, Marcin Grzegorzek
Movement analysis of infants' body parts is momentous for the early detection of various movement disorders such as cerebral palsy. Most existing techniques are either marker-based or use wearable sensors to analyze the movement disorders. Such techniques work well for adults, however they are not effective for infants as wearing such sensors or markers may cause discomfort to them, affecting their natural movements. This paper presents a method to help the clinicians for the early detection of movement disorders in infants...
September 21, 2018: Sensors
Vinay Sehgal, Avi Rosenfeld, David G Graham, Gideon Lipman, Raf Bisschops, Krish Ragunath, Manuel Rodriguez-Justo, Marco Novelli, Matthew R Banks, Rehan J Haidry, Laurence B Lovat
Introduction: Barrett's oesophagus (BE) is a precursor to oesophageal adenocarcinoma (OAC). Endoscopic surveillance is performed to detect dysplasia arising in BE as it is likely to be amenable to curative treatment. At present, there are no guidelines on who should perform surveillance endoscopy in BE. Machine learning (ML) is a branch of artificial intelligence (AI) that generates simple rules, known as decision trees (DTs). We hypothesised that a DT generated from recognised expert endoscopists could be used to improve dysplasia detection in non-expert endoscopists...
2018: Gastroenterology Research and Practice
Apoorve Nayyar, Jihane Jadi, Roja Garimella, Stephen Tyler Elkins-Williams, Kristalyn K Gallagher, Loree K Kalliainen, Charles Scott Hultman, Cindy Wu
Background: Social media has become an indispensable tool for patients to learn about aesthetic surgery. Currently, procedure-specific patient preferences for social media platforms and content are unknown. Objectives: To evaluate social media preferences of patients seeking aesthetic surgery. Methods: We utilized a choice-based conjoint analysis survey to analyze the preferences of patients seeking three common aesthetic procedures - breast augmentation (BA), facial rejuvenation (FR) and combined breast/abdominal surgery (BAB)...
September 13, 2018: Aesthetic Surgery Journal
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