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Profil bibliographique

David Dellamonica

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

11Publications signalées
69Citations signalées
2Affiliations récentes

Les institutions déclarées

Les domaines associés

Radiomics and Machine Learning in Medical ImagingAdvances in Oncology and RadiotherapyLung Cancer Treatments and MutationsGlobal Cancer Incidence and ScreeningCancer Genomics and Diagnostics

Les publications récentes

Accès ouvert 2026 article OpenAlex

Retrospective development and external validation of machine learning models for COVID-19 severity prediction in lung and hematological malignancies: evidence of subtype-specific feature selection bias in joint training

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 (code pays fourni par la source)

0 citations BMC Infectious Diseases
Accès ouvert 2026 article OpenAlex

Utilizing Machine Learning to Identify Multimodal Signatures for Patients Who Would Benefit from the Addition of Tremelimumab to Durvalumab and Chemotherapy (TRIDENT)

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 (code pays fourni par la source)

0 citations Clinical Cancer Research
Accès ouvert 2026 article OpenAlex

Data Resource Profile: Prostate cancer data from Clinical Practice Research Datalink linked hospital records, mortality data and cancer registry standardized to the Observational Medical Outcomes Partnership common data model (CPRD-PCa-OMOP)

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 (code pays fourni par la source)

0 citations International Journal of Epidemiology
Accès ouvert 2025 article OpenAlex

The AI revolution: how multimodal intelligence will reshape the oncology ecosystem

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 (code pays fourni par la source)

11 citations npj Artificial Intelligence
Accès ouvert 2025 article OpenAlex

Prediction of real-world progression free survival (rwPFS) using a multimodal machine learning (ML) model for patients with HR+ HER2- metastatic breast cancer (mBC) undergoing first line (1L) treatment with cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) and endocrine therapy (ET).

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 (code pays fourni par la source)

1 citation Journal of Clinical Oncology
Accès ouvert 2024 article OpenAlex

Trends in incidence, prevalence, and survival of breast cancer in the United Kingdom from 2000 to 2021

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 (code pays fourni par la source)

28 citations Scientific Reports
2024 conference-abstract OpenAlex

Similarities and differences of lung cancer (LC) multidisciplinary teams (MDTs) in China compared to Europe and Canada.

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 (code pays fourni par la source)

1 citation Journal of Clinical Oncology
Accès ouvert 2024 article OpenAlex

Enhancing Multidisciplinary Team Processes in Lung Cancer Care: A Self-Assessment Toolkit and Best Practices

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 (code pays fourni par la source)

0 citations Journal of Clinical Pathways
2023 conference-abstract OpenAlex

Best practices study to enhance the quality of multi-disciplinary teams in lung cancer care.

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 (code pays fourni par la source)

0 citations Journal of Clinical Oncology
Accès ouvert 2021 article OpenAlex

Can machine learning bring cardiovascular risk assessment to the next level? A methodological study using FOURIER trial data

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 (code pays fourni par la source)

25 citations European Heart Journal - Digital Health
2019 article OpenAlex

P6420Can machine learning help us improve risk stratification of diabetic patients with acute coronary syndromes? The answer will blow your mind

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 (code pays fourni par la source)

3 citations European Heart Journal

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