Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Meysam Ahangaran"'
Autor:
Meysam Ahangaran, Hanzhi Zhu, Ruihui Li, Lingkai Yin, Joseph Jang, Arnav P. Chaudhry, Lindsay A. Farrer, Rhoda Au, Vijaya B. Kolachalama
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Background Machine learning (ML) has emerged as the predominant computational paradigm for analyzing large-scale datasets across diverse domains. The assessment of dataset quality stands as a pivotal precursor to the successful deployment of
Externí odkaz:
https://doaj.org/article/00ecab8174a34c79b9c6c56670e2b72a
Publikováno v:
Network Modeling Analysis in Health Informatics and Bioinformatics. 11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf5676f0e8fe3182cbf01859050e0157
https://doi.org/10.1007/s13721-022-00386-y
https://doi.org/10.1007/s13721-022-00386-y
Autor:
Meysam Ahangaran, Adriano Chiò, Fabrizio D'Ovidio, Umberto Manera, Rosario Vasta, Antonio Canosa, Cristina Moglia, Andrea Calvo, Behrouz Minaei-Bidgoli, Mohammad-Reza Jahed-Motlagh
Publikováno v:
Computer methods and programs in biomedicine. 216
Recent advances in the genetic causes of ALS reveals that about 10% of ALS patients have a genetic origin and that more than 30 genes are likely to contribute to this disease. However, four genes are more frequently associated with ALS: C9ORF72, TARD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abf0b339abb99375039de9fc91d46a84
https://pubmed.ncbi.nlm.nih.gov/35151113
https://pubmed.ncbi.nlm.nih.gov/35151113
One of the key challenges for classifying multiple cancer types is the complexity of Tumor Protein p53 mutation patterns and its individual effects on tumors. However, far too little attention has been paid to Deep reinforcement Learning on TP53 muta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68ea4e193e8befb23d2b67df5a31a7e1
https://doi.org/10.21203/rs.3.rs-744748/v1
https://doi.org/10.21203/rs.3.rs-744748/v1
Publikováno v:
Applied Soft Computing. 53:1-18
Cellular learning automata (CLA) is a distributed computational model which was introduced in the last decade. This model combines the computational power of the cellular automata with the learning power of the learning automata. Cellular learning au
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e9cc1e5ec58d8aa0435874107f61be7
https://doi.org/10.1016/j.asoc.2016.12.006
https://doi.org/10.1016/j.asoc.2016.12.006
Publikováno v:
Artificial Intelligence in Medicine. 107:101879
Causal discovery is considered as a major concept in biomedical informatics contributing to diagnosis, therapy, and prognosis of diseases. Probabilistic causality approaches in epidemiology and medicine is a common method for finding relationships be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::693bb750e0db98e696fff3254b12ccac
https://doi.org/10.1016/j.artmed.2020.101879
https://doi.org/10.1016/j.artmed.2020.101879
Publikováno v:
Journal of biomedical informatics. 89
One of the most important issues in predictive modeling is to determine major cause factors of a phenomenon and causal relationships between them. Extracting causal relationships between parameters in a natural phenomenon can be accomplished through
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ea39493eb094ce2e123438004d2b5a9
https://pubmed.ncbi.nlm.nih.gov/30339928
https://pubmed.ncbi.nlm.nih.gov/30339928