Accès ouvert
2026
article
OpenAlex
Frederik Trinkmann, Nikos Paragios, Jean‐Yves Blay, Hugo Crochet et autres
Patients with lung or hematological malignancies face an elevated risk of severe COVID-19 outcomes. While machine learning frameworks offer predictive utility, training a single joint clinical-biological model on heterogeneous cancer populations can introduce structural feature selection bias, limiting clinical generalizability. Utilizing a …
de, fr, us, gb
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Accès ouvert
2026
article
OpenAlex
Ferdinandos Skoulidis, Salma K. Jabbour, Edward B. Garon, Puneeth Iyengar et autres
PURPOSE: POSEIDON (NCT03164616) was a randomized, open-label, multicenter phase 3 trial comparing first-line durvalumab with or without tremelimumab in combination with chemotherapy versus chemotherapy alone in patients with metastatic non-small-cell lung cancer (NSCLC). Overall survival (OS) and progression-free survival were significantly increased …
us, it, fr, ch, jp, es, gb
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Accès ouvert
2026
article
OpenAlex
Eng Hooi Tan, Danielle Newby, Daniel Prieto‐Alhambra, Mandickel Kamtengeni et autres
CPRD-PCa-OMOP comprises men from England with incident prostate cancer (PCa) selected from the Clinical Practice Research Datalink (CPRD) GOLD and Aurum primary care databases, linked to hospital admissions, Office for National Statistics mortality data, and national cancer registry records. Each dataset was …
gb, nl
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Accès ouvert
2025
article
OpenAlex
David Dellamonica, David Ruau, Greg Rossi, Bob T. Li et autres
Abstract Multimodal artificial intelligence (MMAI) is redefining oncology by integrating heterogeneous datasets from diagnostic modalities into cohesive analytical frameworks for more accurate and personalized cancer care. We highlight MMAI applications across the patient journey and clinical research, discuss outstanding challenges, and the …
ch, us, gb, es
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Accès ouvert
2025
article
OpenAlex
Pedram Razavi, Julia An, Tatiana Erazo, Paul Schwartz et autres
e13088 Background: CDK4/6i combined with ET is 1L standard of care treatment for HR+/HER2- for mBC patients, however duration of response varies with some patients experiencing disease progression within 12-months. Limited predictive factors related to ET+CDK4/6i treatment response exist. This pilot aims …
us, fr, ch, es, jp, gb
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Accès ouvert
2024
article
OpenAlex
Nicola L. Barclay, Edward Burn, Antonella Delmestri, Talita Duarte‐Salles et autres
Breast cancer is the most frequently diagnosed cancer in females globally. However, we know relatively little about trends in males. This study describes United Kingdom (UK) secular trends in breast cancer from 2000 to 2021 for both sexes. We describe a population-based …
gb, es, us, bd, cz, nl, de, se, fr, ee, it, at, be
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2024
conference-abstract
OpenAlex
Poka Yingjing Cui, Bichai Yin, Yichen Zhang, Yi‐Long Wu et autres
e13562 Background: LC MDTs involve a collaborative approach where specialists work together to analyze individual cases, discuss treatment options, and tailor comprehensive care plans for patients. Implementing MDTs can be challenging, especially for developing countries with limited resources and high disease burden. …
cn, us, ch, es
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Accès ouvert
2024
article
OpenAlex
Poka Yingjing Cui, Peter Blanshard, María Teresa Campos-Partera, Adrien Moucquot et autres
Multidisciplinary teams (MDTs) play a pivotal role in the comprehensive management of cancer. MDT meetings (MDTMs) bring together specialized experts across the entire patient care spectrum, convening regularly to discuss patient cases, select optimal diagnostic strategies, and determine the most appropriate treatment …
pt, gb
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2023
conference-abstract
OpenAlex
M. Gallego-Llorente, Lidewey Verbaas, Yingjing Poka Cui, Marcio M. Gomes et autres
1532 Background: Regular meetings at multi-disciplinary teams (MDTs) constitute a key moment in the care pathway in lung cancer, where physicians collectively discuss patient cases and decide on treatment plans. MDTs arguably increase the volume of patients treated, improve diagnosis, and positively …
ca, ch
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Accès ouvert
2021
article
OpenAlex
A. Rousset, David Dellamonica, Romuald Menuet, Armando Lira Pineda et autres
Abstract Aims Through this proof of concept, we studied the potential added value of machine learning (ML) methods in building cardiovascular risk scores from structured data and the conditions under which they outperform linear statistical models. Methods and results Relying on extensive …
ch, us
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2019
article
OpenAlex
Jaques S. Milner, Sílvia Monteiro, Pedro Monteiro, Meng Xiao He et autres
Abstract Background Risk stratification following an acute coronary syndrome (ACS) is of utmost importance, in order to identify patients at higher risk of subsequent cardiovascular events. Diabetic patients have a significantly worse prognosis, so new risk prediction tools are important to better …
nl
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