Zobrazeno 1 - 10
of 1 148
pro vyhledávání: '"Abu‐Hanna, Ameen"'
Detecting out-of-distribution (OOD) instances is crucial for the reliable deployment of machine learning models in real-world scenarios. OOD inputs are commonly expected to cause a more uncertain prediction in the primary task; however, there are OOD
Externí odkaz:
http://arxiv.org/abs/2405.12658
Generating high-quality summaries for chat dialogs often requires large labeled datasets. We propose a method to efficiently use unlabeled data for extractive summarization of customer-agent dialogs. In our method, we frame summarization as a questio
Externí odkaz:
http://arxiv.org/abs/2311.11462
Autor:
Kom, Izak Yasrebi-de, Klopotowska, Joanna, Dongelmans, Dave, De Keizer, Nicolette, Jager, Kitty, Abu-Hanna, Ameen, Cinà, Giovanni
The current best practice approach for the retrospective diagnosis of adverse drug events (ADEs) in hospitalized patients relies on a full patient chart review and a formal causality assessment by multiple medical experts. This evaluation serves to q
Externí odkaz:
http://arxiv.org/abs/2311.09137
Despite their success, Machine Learning (ML) models do not generalize effectively to data not originating from the training distribution. To reliably employ ML models in real-world healthcare systems and avoid inaccurate predictions on out-of-distrib
Externí odkaz:
http://arxiv.org/abs/2309.16220
Availability of diagnostic codes in Electronic Health Records (EHRs) is crucial for patient care as well as reimbursement purposes. However, entering them in the EHR is tedious, and some clinical codes may be overlooked. Given an in-complete list of
Externí odkaz:
http://arxiv.org/abs/2305.04992
We investigate different natural language processing (NLP) approaches based on contextualised word representations for the problem of early prediction of lung cancer using free-text patient medical notes of Dutch primary care physicians. Because lung
Externí odkaz:
http://arxiv.org/abs/2303.15846
Autor:
Rios, Miguel, Abu-Hanna, Ameen
Intensive Care in-hospital mortality prediction has various clinical applications. Neural prediction models, especially when capitalising on clinical notes, have been put forward as improvement on currently existing models. However, to be acceptable
Externí odkaz:
http://arxiv.org/abs/2212.06267
Autor:
Rios, Miguel, Abu-Hanna, Ameen
Neural models, with their ability to provide novel representations, have shown promising results in prediction tasks in healthcare. However, patient demographics, medical technology, and quality of care change over time. This often leads to drop in t
Externí odkaz:
http://arxiv.org/abs/2212.00557
Autor:
Medlock, Stephanie, Eslami, Saeid, Askari, Marjan, Arts, Derk L, Sent, Danielle, de Rooij, Sophia E, Abu-Hanna, Ameen
Publikováno v:
Journal of Medical Internet Research, Vol 17, Iss 1, p e10 (2015)
BackgroundThe Internet is viewed as an important source for health information and a medium for patient empowerment. However, little is known about how seniors use the Internet in relation to other sources for health information. ObjectiveThe aim wa
Externí odkaz:
https://doaj.org/article/ea4a3baec0204eb99e6c1cc81ad8db05
