Zobrazeno 1 - 10
of 697
pro vyhledávání: '"Riegler, Michael"'
Extracting meaningful insights from large and complex datasets poses significant challenges, particularly in ensuring the accuracy and relevance of retrieved information. Traditional data retrieval methods such as sequential search and index-based re
Externí odkaz:
http://arxiv.org/abs/2409.17580
Autor:
Gautam, Sushant, Storås, Andrea, Midoglu, Cise, Hicks, Steven A., Thambawita, Vajira, Halvorsen, Pål, Riegler, Michael A.
We introduce Kvasir-VQA, an extended dataset derived from the HyperKvasir and Kvasir-Instrument datasets, augmented with question-and-answer annotations to facilitate advanced machine learning tasks in Gastrointestinal (GI) diagnostics. This dataset
Externí odkaz:
http://arxiv.org/abs/2409.01437
Autor:
Jha, Debesh, Tomar, Nikhil Kumar, Sharma, Vanshali, Trinh, Quoc-Huy, Biswas, Koushik, Pan, Hongyi, Jha, Ritika K., Durak, Gorkem, Hann, Alexander, Varkey, Jonas, Dao, Hang Viet, Van Dao, Long, Nguyen, Binh Phuc, Pham, Khanh Cong, Tran, Quang Trung, Papachrysos, Nikolaos, Rieders, Brandon, Schmidt, Peter Thelin, Geissler, Enrik, Berzin, Tyler, Halvorsen, Pål, Riegler, Michael A., de Lange, Thomas, Bagci, Ulas
Colonoscopy is the primary method for examination, detection, and removal of polyps. Regular screening helps detect and prevent colorectal cancer at an early curable stage. However, challenges such as variation among the endoscopists' skills, bowel q
Externí odkaz:
http://arxiv.org/abs/2409.00045
Missing data is a prevalent issue that can significantly impair model performance and interpretability. This paper briefly summarizes the development of the field of missing data with respect to Explainable Artificial Intelligence and experimentally
Externí odkaz:
http://arxiv.org/abs/2407.00411
Autor:
Sheshkal, Sajad Amouei, Gundersen, Morten, Riegler, Michael Alexander, Utheim, Øygunn Aass, Gundersen, Kjell Gunnar, Hammer, Hugo Lewi
Dry eye disease is a common disorder of the ocular surface, leading patients to seek eye care. Clinical signs and symptoms are currently used to diagnose dry eye disease. Metabolomics, a method for analyzing biological systems, has been found helpful
Externí odkaz:
http://arxiv.org/abs/2406.14068
Autor:
Gautam, Sushant, Sarkhoosh, Mehdi Houshmand, Held, Jan, Midoglu, Cise, Cioppa, Anthony, Giancola, Silvio, Thambawita, Vajira, Riegler, Michael A., Halvorsen, Pål, Shah, Mubarak
The application of Automatic Speech Recognition (ASR) technology in soccer offers numerous opportunities for sports analytics. Specifically, extracting audio commentaries with ASR provides valuable insights into the events of the game, and opens the
Externí odkaz:
http://arxiv.org/abs/2405.07354
Understanding sleep and activity patterns plays a crucial role in physical and mental health. This study introduces a novel approach for sleep detection using weakly supervised learning for scenarios where reliable ground truth labels are unavailable
Externí odkaz:
http://arxiv.org/abs/2402.17601
Missing data is a common problem in practical data science settings. Various imputation methods have been developed to deal with missing data. However, even though the labels are available in the training data in many situations, the common practice
Externí odkaz:
http://arxiv.org/abs/2311.16877
Autor:
Jha, Debesh, Sharma, Vanshali, Banik, Debapriya, Bhattacharya, Debayan, Roy, Kaushiki, Hicks, Steven A., Tomar, Nikhil Kumar, Thambawita, Vajira, Krenzer, Adrian, Ji, Ge-Peng, Poudel, Sahadev, Batchkala, George, Alam, Saruar, Ahmed, Awadelrahman M. A., Trinh, Quoc-Huy, Khan, Zeshan, Nguyen, Tien-Phat, Shrestha, Shruti, Nathan, Sabari, Gwak, Jeonghwan, Jha, Ritika K., Zhang, Zheyuan, Schlaefer, Alexander, Bhattacharjee, Debotosh, Bhuyan, M. K., Das, Pradip K., Fan, Deng-Ping, Parsa, Sravanthi, Ali, Sharib, Riegler, Michael A., Halvorsen, Pål, De Lange, Thomas, Bagci, Ulas
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such
Externí odkaz:
http://arxiv.org/abs/2307.16262
Autor:
Jha, Debesh, Sharma, Vanshali, Dasu, Neethi, Tomar, Nikhil Kumar, Hicks, Steven, Bhuyan, M. K., Das, Pradip K., Riegler, Michael A., Halvorsen, Pål, Bagci, Ulas, de Lange, Thomas
Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, biased outcomes, data quality, lack of transparency, and underperformanc
Externí odkaz:
http://arxiv.org/abs/2307.08140