Zobrazeno 1 - 10
of 2 632
pro vyhledávání: '"SURVIVAL PREDICTION"'
Autor:
Seyedeh Zahra Hamedi, Hassan Emami, Maryam Khayamzadeh, Reza Rabiei, Mehrad Aria, Majid Akrami, Vahid Zangouri
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Breast cancer is one of the most prevalent cancers with an increasing trend in both incidence and mortality rates in Iran. Survival analysis is a pivotal measure in setting appropriate care plans. To the best of our knowledge, this study is
Externí odkaz:
https://doaj.org/article/aca6652bb2304c26b77d2e6964571824
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Squamous cell lung cancer (SQCLC), which is fatal to humans, is heterogeneous with different genetic and histological features. We used SBMOI, a multi-omics data integration method from previous study, to integrate clinical, gene expression,
Externí odkaz:
https://doaj.org/article/5a35b635426d45168e6376488fab8811
Autor:
Blanca Ferrer-Lores, Alfonso Ortiz-Algarra, Alfonso Picó-Peris, Alejandra Estepa-Fernández, Fuensanta Bellvís-Bataller, Glen J. Weiss, Almudena Fuster-Matanzo, Juan Pedro Fernández, Ana Jimenez-Pastor, Rafael Hernani, Ana Saus-Carreres, Ana Benzaquen, Laura Ventura, José Luis Piñana, Ana Belén Teruel, Alicia Serrano-Alcalá, Rosa Dosdá, Pablo Sopena-Novales, Aitana Balaguer-Rosello, Manuel Guerreiro, Jaime Sanz, Luis Martí-Bonmatí, María José Terol, Ángel Alberich-Bayarri
Publikováno v:
EJNMMI Research, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Background This multicentre retrospective observational study aims to develop imaging-based prognostic and predictive models for relapsed/refractory (R/R) B-cell lymphoma patients undergoing CAR-T therapy by integrating clinical data and ima
Externí odkaz:
https://doaj.org/article/0057ba293b9c45989ef0c7a2fb4073b2
Autor:
Sacha Davis, Russell Greiner
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Background The rate of 30-day all-cause hospital readmissions can affect the funding a hospital receives. An accurate and reliable readmission prediction model could save money and increase quality-of-care. Few projects have explored formula
Externí odkaz:
https://doaj.org/article/85286db65ca74852a5cf6729b80a24c3
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Breast cancer (BC) is a major contributor to female mortality worldwide, particularly in young women with aggressive tumors. Despite the need for accurate prognosis in this demographic, existing studies primarily focus on broader age groups,
Externí odkaz:
https://doaj.org/article/3f7c5e0a300e4ac5b9f395df72fd7972
Autor:
G. S. Pradeep Ghantasala, Kumar Dilip, Pellakuri Vidyullatha, Sarah Allabun, Mohammed S. Alqahtani, Manal Othman, Mohamed Abbas, Ben Othman Soufiene
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Ovarian cancer is a formidable health challenge that demands accurate and timely survival predictions to guide clinical interventions. Existing methods, while commendable, suffer from limitations in harnessing the temporal evolution of patie
Externí odkaz:
https://doaj.org/article/cdcfbf905a704369b59d1970355d963e
Autor:
Takayuki Sakurai, Tetsuo Saito, Kohsei Yamaguchi, Shigeyuki Takamatsu, Satoshi Kobayashi, Naoki Nakamura, Natsuo Oya
Publikováno v:
Radiation Oncology, Vol 19, Iss 1, Pp 1-7 (2024)
Abstract Background The 3-variable number-of-risk-factors (NRF) model is a prognostic tool for patients undergoing palliative radiotherapy (PRT). However, there is little research on the NRF model for patients with painful non-bone-metastasis tumours
Externí odkaz:
https://doaj.org/article/d2eec8dd82684bdfb60e7135e34b7df3
Publikováno v:
Asian Journal of Surgery, Vol 47, Iss 10, Pp 4412-4416 (2024)
Externí odkaz:
https://doaj.org/article/164240b84f964e33b28b6e36ce7f9f6e
Autor:
Jie Lian, Fan Huang, Xinhai Huang, Kitty Yu-Yeung Lau, Kei Shing Ng, Carlin Chun Fai Chu, Simon Ching Lam, Mohamad Koohli-Moghadam, Varut Vardhanabhuti
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background Predicting an individual’s risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes buildin
Externí odkaz:
https://doaj.org/article/20984507519c41459606b435c1104f6f
Autor:
M. Yeghaian, Z. Bodalal, T.M. Tareco Bucho, I. Kurilova, C.U. Blank, E.F. Smit, M.S. van der Heijden, T.D.L. Nguyen-Kim, D. van den Broek, R.G.H. Beets-Tan, S. Trebeschi
Publikováno v:
Immuno-Oncology and Technology, Vol 24, Iss , Pp 100723- (2024)
Background: Integrating complementary diagnostic data sources promises enhanced robustness in the predictive performance of artificial intelligence (AI) models, a crucial requirement for future clinical validation/implementation. In this study, we in
Externí odkaz:
https://doaj.org/article/5f5317e81b0641389facd258726adf33