Tebbens, Ricardo (author)
There is a raising demand for player statistics in the world of football. With the developments over the last years in wearable sensors, Human Activity Recognition (HAR) based on wearable IMU sensors can be used to tackle this problem. This thesis builds upon an earlier research done for this topic, where an end-to-end pipeline based on deep learni...
Xu, Sheng-Ming Dong, Dong Li, Wei Bai, Tian Zhu, Ming-Zhu Gu, Gui-Shan
Published in
World journal of clinical cases
Femoral trochlear dysplasia (FTD) is an important risk factor for patellar instability. Dejour classification is widely used at present and relies on standard lateral X-rays, which are not common in clinical work. Therefore, magnetic resonance imaging (MRI) has become the first choice for the diagnosis of FTD. However, manually measuring is tedious...
Zheng, J Yuan, S Wu, W Li, W Yu, L Fu, H Coomes, D
Coconut (Cocos nucifera L.) is one of the world's most economically important tree species, and coconut palm plantations dominate many islands and tropical coastlines. However, the expansion of plantations to supply international markets threatens biodiversity. Therefore, monitoring the plantations is important not only for the food industry but al...
Wang, Yun Fei Mao, Li Chen, Hui Juan Yang, Yu Ting Li, Xiu Li Lu, Guang Ming Xing, Wei Zhang, Long Jiang
Published in
Progress in neuro-psychopharmacology & biological psychiatry
To develop and validate artificial intelligence models for the prediction of cognitive impairment in chronic kidney disease (CKD) patients using structural and functional brain network. This study retrospectively recruited 621 CKD patients and 625 healthy controls in Jinling hospital and 57 CKD patients in Hainan hospital. These CKD patients were d...
Nespolo, Rogerio Garcia Yi, Darvin Cole, Emily Wang, Daniel Warren, Alexis Leiderman, Yannek I
Published in
Ophthalmology. Retina
This study investigated whether a deep-learning neural network can detect and segment surgical instrumentation and relevant tissue boundaries and landmarks within the retina using imaging acquired from a surgical microscope in real time, with the goal of providing image-guided vitreoretinal (VR) microsurgery. Retrospective analysis via a prospectiv...
Fung, Timothy H M John, Neville C R A Guillemaut, Jean-Yves Yorston, David Frohlich, David Steel, David H W Williamson, Tom H
Published in
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
To develop and evaluate an automated deep learning model to predict the anatomical outcome of rhegmatogenous retinal detachment (RRD) surgery. Six thousand six hundred and sixty-one digital images of RRD treated by vitrectomy and internal tamponade were collected from the British and Eire Association of Vitreoretinal Surgeons database. Each image w...
LoGiudice, Andrew B Norman, Geoffrey R Manzoor, Saba Monteiro, Sandra
Published in
Advances in health sciences education : theory and practice
Students are often encouraged to learn 'deeply' by abstracting generalizable principles from course content rather than memorizing details. So widespread is this perspective that Likert-style inventories are now routinely administered to students to quantify how much a given course or curriculum evokes deep learning. The predictive validity of thes...
Delplanque, Alexandre Foucher, Samuel Théau, Jérôme Bussière, Elsa Vermeulen, Cédric Lejeune, Philippe
peer reviewed / Rapid growth of human populations in sub-Saharan Africa has led to a simultaneous increase in the number of livestock, often leading to conflicts of use with wildlife in protected areas. To minimize these conflicts, and to meet both communities’ and conservation goals, it is therefore essential to monitor livestock density and their...
Laplante, Simon Namazi, Babak Kiani, Parmiss Hashimoto, Daniel A Alseidi, Adnan Pasten, Mauricio Brunt, L Michael Gill, Sujata Davis, Brian Bloom, Matthew
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Published in
Surgical endoscopy
Many surgical adverse events, such as bile duct injuries during laparoscopic cholecystectomy (LC), occur due to errors in visual perception and judgment. Artificial intelligence (AI) can potentially improve the quality and safety of surgery, such as through real-time intraoperative decision support. GoNoGoNet is a novel AI model capable of identify...
Kobayashi, Satoshi King, Franklin Hata, Nobuhiko
Published in
International journal of computer assisted radiology and surgery
Understanding the three-dimensional anatomy of percutaneous intervention in prostate cancer is essential to avoid complications. Recently, attempts have been made to use machine learning to automate the segmentation of functional structures such as the prostate gland, rectum, and bladder. However, a paucity of material is available to segment extra...