Zobrazeno 1 - 10
of 50 526
pro vyhledávání: '"Joint model"'
Autor:
Alvares, Danilo, Barrett, Jessica K., Mercier, François, Schulze, Jochen, Yiu, Sean, Castro, Felipe, Roumpanis, Spyros, Zhu, Yajing
Joint models have proven to be an effective approach for uncovering potentially hidden connections between various types of outcomes, mainly continuous, time-to-event, and binary. Typically, longitudinal continuous outcomes are characterized by linea
Externí odkaz:
http://arxiv.org/abs/2407.14311
Dementia currently affects about 50 million people worldwide, and this number is rising. Since there is still no cure, the primary focus remains on preventing modifiable risk factors such as cardiovascular factors. It is now recognized that high bloo
Externí odkaz:
http://arxiv.org/abs/2408.06769
Time-triggered federated learning, in contrast to conventional event-based federated learning, organizes users into tiers based on fixed time intervals. However, this network still faces challenges due to a growing number of devices and limited wirel
Externí odkaz:
http://arxiv.org/abs/2408.01765
Autor:
Alvares, Danilo, Barrett, Jessica K., Mercier, François, Roumpanis, Spyros, Yiu, Sean, Castro, Felipe, Schulze, Jochen, Zhu, Yajing
Predicting cancer-associated clinical events is challenging in oncology. In Multiple Myeloma (MM), a cancer of plasma cells, disease progression is determined by changes in biomarkers, such as serum concentration of the paraprotein secreted by plasma
Externí odkaz:
http://arxiv.org/abs/2405.20418
Autor:
Afonso, Pedro Miranda, Rizopoulos, Dimitris, Palipana, Anushka K., Gecili, Emrah, Brokamp, Cole, Clancy, John P., Szczesniak, Rhonda D., Andrinopoulou, Eleni-Rosalina
Joint models for longitudinal and survival data have become a popular framework for studying the association between repeatedly measured biomarkers and clinical events. Nevertheless, addressing complex survival data structures, especially handling bo
Externí odkaz:
http://arxiv.org/abs/2405.16492
Anonymizing the GPS locations of observations can bias a spatial model's parameter estimates and attenuate spatial predictions when improperly accounted for, and is relevant in applications from public health to paleoseismology. In this work, we demo
Externí odkaz:
http://arxiv.org/abs/2405.04928
In applications such as biomedical studies, epidemiology, and social sciences, recurrent events often co-occur with longitudinal measurements and a terminal event, such as death. Therefore, jointly modeling longitudinal measurements, recurrent events
Externí odkaz:
http://arxiv.org/abs/2404.03804
The results of information retrieval (IR) are usually presented in the form of a ranked list of candidate documents, such as web search for humans and retrieval-augmented generation for large language models (LLMs). List-aware retrieval aims to captu
Externí odkaz:
http://arxiv.org/abs/2402.02764
Introduction: Heterogeneity of the progression of neurodegenerative diseases is one of the main challenges faced in developing effective therapies. With the increasing number of large clinical databases, disease progression models have led to a bette
Externí odkaz:
http://arxiv.org/abs/2401.17249
Publikováno v:
Transactions of the Chinese Society of Agricultural Engineering. Jul2024, Vol. 40 Issue 13, p156-162. 7p.