Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Luca Putelli"'
Publikováno v:
IEEE Access, Vol 12, Pp 162651-162667 (2024)
The analysis of the presence of bias, prejudices and unwanted discriminatory behavior in pre-trained neural language models (NLMs), considering the sensitivity of the topic and its public interest, should respect two main criteria: the intuition and
Externí odkaz:
https://doaj.org/article/25645da4e4b84bf788809ac8216a3ed5
Autor:
Matteo Olivato, Luca Putelli, Nicola Arici, Alfonso Emilio Gerevini, Alberto Lavelli, Ivan Serina
Publikováno v:
IEEE Access, Vol 12, Pp 69710-69727 (2024)
Radiology reports are a valuable source of textual information used to improve clinical care and support research. In recent years, deep learning techniques have been shown to be effective in classifying radiology reports. This article investigates t
Externí odkaz:
https://doaj.org/article/605b08f88a6f43fcbdc7718353eab8e5
Publikováno v:
IEEE Access, Vol 11, Pp 83905-83933 (2023)
AI and Machine Learning (ML) offer powerful tools to support clinical decision making in emergency situations such as the COVID-19 pandemic. In this context, the application of ML requires to design predictive systems that have adequate accuracy and
Externí odkaz:
https://doaj.org/article/ea9202cb93834382951245b83f51d269
Autor:
Nicola Arici, Alfonso Emilio Gerevini, Matteo Olivato, Luca Putelli, Luca Sigalini, Ivan Serina
Publikováno v:
Future Internet, Vol 15, Iss 8, p 268 (2023)
Artificial Intelligence and Natural Language Processing techniques can have a very significant impact on the e-learning sector, with the introduction of chatbots, automatic correctors, or scoring systems. However, integrating such technologies into t
Externí odkaz:
https://doaj.org/article/d24e436dbb1e44009ff3285ab22113a3
Publikováno v:
Future Internet, Vol 15, Iss 7, p 230 (2023)
In recent years, many studies have been devoted to discovering the inner workings of Transformer-based models, such as BERT, for instance, attempting to identify what information is contained within them. However, little is known about how these mode
Externí odkaz:
https://doaj.org/article/f6c3e41dbc09459ba652b1c776b32117
Publikováno v:
Future Internet, Vol 15, Iss 2, p 79 (2023)
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, e.g., relation extraction and semantic search. Extracting the text of interest from biomedical documents becomes more demanding as the availability of online dat
Externí odkaz:
https://doaj.org/article/913f3824cbf84e368b4c4d23c0c84f4d
Publikováno v:
Future Internet, Vol 14, Iss 2, p 62 (2022)
During the COVID-19 pandemic, the corporate online training sector has increased exponentially and online course providers had to implement innovative solutions to be more efficient and provide a satisfactory service. This paper considers a real case
Externí odkaz:
https://doaj.org/article/530f14bd4c0a44a696448a1afbc7adbd
Autor:
Matteo Olivato, Nicholas Rossetti, Alfonso E. Gerevini, Mattia Chiari, Luca Putelli, Ivan Serina
During 2020 and 2021, managing limited healthcare resources and hospital beds has been a fundamental aspect of the fight against the COVID-19 pandemic. Predicting in advance the length of stay, and in particular identifying whether a patient is going
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e53056f83ddf2423d945c6d36e308c9e
https://hdl.handle.net/11379/568327
https://hdl.handle.net/11379/568327
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687625
ICPR Workshops (1)
ICPR Workshops (1)
The recent spread of COVID-19 put a strain on hospitals all over the world. In this paper we address the problem of hospital overloads and present a tool based on machine learning to predict the length of stay of hospitalised patients affected by COV
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5985798de764f43490c0f054cae276f
https://doi.org/10.1007/978-3-030-68763-2_16
https://doi.org/10.1007/978-3-030-68763-2_16
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9783030772109
AIME
AIME
Although deep learning techniques have obtained remarkable results in clinical text analysis, the delicacy of this application domain requires also that these models can be easily understood by the hospital staff. The attention mechanism, which assig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef0da8021c8919a23048c52e90d34cc6
https://doi.org/10.1007/978-3-030-77211-6_42
https://doi.org/10.1007/978-3-030-77211-6_42