Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Mark J. Carman"'
Publikováno v:
Computational Linguistics (2023)
Externí odkaz:
https://doaj.org/article/82b8be660ae143a1bfcb989a8a56b839
Publikováno v:
Database : the journal of biological databases and curation. 2022
The Gene Expression Omnibus (GEO) is a public archive containing >4 million digital samples from functional genomics experiments collected over almost two decades. The accompanying metadata describing the experiments suffer from redundancy, inconsist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f74e8819137e72d889f3eaa13787330a
https://pubmed.ncbi.nlm.nih.gov/35657113
https://pubmed.ncbi.nlm.nih.gov/35657113
Publikováno v:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track-European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track
Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track ISBN: 9783030676698
ECML/PKDD (5)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track
Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track ISBN: 9783030676698
ECML/PKDD (5)
While exponential growth in public genomic data can afford great insights into biological processes underlying diseases, a lack of structured metadata often impedes its timely discovery for analysis. In the Gene Expression Omnibus, for example, descr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a8952e1637180dfdfbe590e2fec04c3
Autor:
Marco Masseroli, Mark J. Carman, Silvia Cascianelli, Francisco Cristovao, Pietro Pinoli, Arif Canakoglu, Luca Nanni
Publikováno v:
IEEE/ACM transactions on computational biology and bioinformatics. 19(1)
Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification methods rely on the expression quantification of small gene sets. Next Generation Sequencing promises large amounts of omic data in the next years. In this sce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::078182387e769fe813f1ef4082f93db3
https://pubmed.ncbi.nlm.nih.gov/33270566
https://pubmed.ncbi.nlm.nih.gov/33270566
Publikováno v:
Pattern Recognition. 83:230-244
Clusters may exist in different subspaces of a multidimensional dataset. Traditional full-space clustering algorithms have difficulty in identifying these clusters. Various subspace clustering algorithms have used different subspace search strategies
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2c357080a8cc5f4af2794ca21cff05d
https://doi.org/10.1016/j.patcog.2018.05.027
https://doi.org/10.1016/j.patcog.2018.05.027
Publikováno v:
Pattern Recognition. 117:107977
The problem of inhomogeneous cluster densities has been a long-standing issue for distance-based and density-based algorithms in clustering and anomaly detection. These algorithms implicitly assume that all clusters have approximately the same densit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::244573373cd7e40b415b5ed7a0046709
https://doi.org/10.1016/j.patcog.2021.107977
https://doi.org/10.1016/j.patcog.2021.107977
Autor:
Barbara Pernici, Amudha Ravi Shankar, Jose Luis Fernandez Marquez, Virginia Negri, Gabriele Scalia, Dario Scuratti, Donya Rooein, Stefano Agresti, Mark J. Carman
Publikováno v:
2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS)
ICSE-SEIS
ICSE-SEIS
Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, gi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dffb90a474ad58b1e3093faa6ae4d1f
Autor:
Mark J. Carman, Pietro Pinoli, Francisco Cristovao, Luca Nanni, Silvia Cascianelli, Marco Masseroli, Arif Canakoglu
Publikováno v:
Computational Intelligence Methods for Bioinformatics and Biostatistics ISBN: 9783030630607
CIBB
CIBB
We investigate the important clinical problem of predicting prognosis-related breast cancer molecular subtypes using whole-transcriptome information present in The Cancer Genome Atlas Project (TCGA) dataset. From a Machine Learning perspective, the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05081e657418dbe77be56f6f7263b4ff
http://hdl.handle.net/11311/1159916
http://hdl.handle.net/11311/1159916
A lack of reliable relevance labels for training ranking functions is a significant problem for many search applications. Transfer ranking is a technique aiming to transfer knowledge from an existing machine learning ranking task to a new ranking tas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51af48e5de34a1d81b5a41eedc59303f
http://hdl.handle.net/11311/1145131
http://hdl.handle.net/11311/1145131
Publikováno v:
ICDAR
Texts in Indic Languages contain a large proportion of out-of-vocabulary (OOV) words due to frequent fusion using conjoining rules (of which there are around 4000 in Sanskrit). OCR errors further accentuate this complexity for the error correction sy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41b2fa540d9b51b216fa55003efc29ea
https://doi.org/10.1109/icdar.2019.00034
https://doi.org/10.1109/icdar.2019.00034