Results 91 to 100 of about 342,086 (247)

Natural Killer Cells in Paediatric Soft Tissue Sarcomas: A Systematic Review

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Paediatric soft tissue sarcomas (pSTS) are a rare and heterogeneous group of malignant tumours arising in tissues of mesenchymal origin. The role of natural killer (NK) cells in pSTS remains poorly understood, with evidence fragmented across small preclinical studies and early‐phase clinical trials.
Raya Dean, Lara V. Graham, Christina Putnam, Rosa Gomes Alves Martins, Daniel T. Harding, Tim J. Underwood, Zoë S. Walters, Matthew D. Blunt   +7 more
wiley   +1 more source

Leveraging Attention-Based Deep Learning in Binary Classification for Early-Stage Breast Cancer Diagnosis

Diagnostics
Background: Breast cancer diagnosis is a global health challenge, requiring innovative methods to improve early detection accuracy and efficiency. This study investigates the integration of attention-based deep learning models with traditional machine ...
Lama A. Aldakhil, Shuaa S. Alharbi, Abdulrahman Aloraini, Haifa F. Alhasson   +3 more
doaj   +1 more source

Mapping Childhood Cancer Care Services in Oceania: Methodological Lessons From the SIOP Global Mapping Programme

Pediatric Blood &Cancer, EarlyView.
ABSTRACT The International Paediatric Oncology Society Global Mapping Programme aims to collect data on global paediatric oncology services by continent, with Africa and Latin America completed. This study reports on the methodology and lessons learned for Oceania, a unique continent with resource disparity across countries, multiple small island ...
Trisha Soosay Raj, Christy Noble, Amy Gray, Daniel C. Moreira, Jennifer Lowe, Maite Gorostegui, Gwenda Anga, Andrew Soma, Milena Lay Dos Santos, Siobhan Cross, Erin Luttrell, Michael Sullivan, Julie Cayrol, Julia Challinor, Neil Ranasinghe, Jordana McLoone, Claire E. Wakefield   +16 more
wiley   +1 more source

A Data-Driven Approach for Autism Spectrum Disorder Screening

IEEE Access
Autism spectrum disorder (ASD) is a brain development condition influenced by genes and environment, with no known cause or cure. The diagnosis is challenging due to the absence of biological markers, requiring various examinations and specialist input ...
Rafael Stubs Parpinelli, Gabriel Lenz Balatka, Max Hupfeld Toviansky, Maisa Fernandes Gomes, Tatiana Moura De Barros Sanches, Higor Dos Santos Alves, Marlon do Amaral Correa, Ismael Antiqueira Costa   +7 more
doaj   +1 more source

AI-enhanced diagnostic model for pulmonary nodule classification

Frontiers in Oncology
BackgroundThe identification of benign and malignant pulmonary nodules (BPN and MPN) can significantly reduce mortality. However, a reliable and validated diagnostic model for clinical decision-making is still lacking.MethodsEnzyme-linked immunosorbent assay and electro chemiluminescent immunoassay were utilized to determine the serum concentrations of
Jifei Chen, Moyu Ming, Shuangping Huang, Xuan Wei, Jinyan Wu, Sufang Zhou, Zhougui Ling   +6 more
openaire   +3 more sources

Development and Implementation of a Disease‐Targeted Storybook as a Clinical Tool for Children With Acute Leukemia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Although significant progress has been made in childhood leukemia survival, healthcare providers, and caregivers often face challenges in explaining this disease to patients. Disease‐targeted storybooks have been proposed as a tool to facilitate the understanding of diagnoses and treatment.
Nutvipha Ummartyotin, Usanarat Anurathapan, Rawiwan Roongpraiwan, Potchanee Dandamrongrak, Siriporn Nakhonchai, Pawin Numthavaj, Vilawan Chirdkiatgumchai   +6 more
wiley   +1 more source

Machine Learning–Driven radiomics on 18 F-FDG PET for glioma diagnosis: a systematic review and meta-analysis

Cancer Imaging
Background Machine learning (ML) applied to radiomics has revolutionized neuro-oncological imaging, yet the diagnostic performance of ML models based specifically on ^18F-FDG PET features in glioma remains poorly characterized.
Ali Shahriari, Sasan Ghazanafar Ahari, Ali Mousavi, Mahdie Sadeghi, Marjan Abbasi, Mahsa Hosseinpour, Asal Mir, Dorrin Zohouri Zanganeh, Hossein Gharedaghi, Saba Ezati, Ali Sareminia, Dina Seyedi, Mahla Shokouhfar, Ali Darzi, Alireza Ghaedamini, Sara Zamani, Farbod Khosravi, Mahsa Asadi Anar   +17 more
doaj   +1 more source

Recent advances in artificial intelligence for melanoma: A review of history, models, datasets, applications, and ethical and legal considerations

Journal of Holistic Integrative Pharmacy
Purpose: Melanoma is one of the most lethal and aggressive forms of skin cancer, often presenting as evolving pigmented lesions. This review aims to examine melanoma from a holistic perspective by evaluating integrative strategies that combine Artificial
Rabinarayan Parhi, Goutam Kumar Jena, Anuj Garg, Mahaveer Dhobi, Sumanta Mondal   +4 more
doaj   +1 more source

Statistical Inference for Diagnostic Classification Models

, 2013
Diagnostic classification models (DCM) are an important recent development in educational and psychological testing. Instead of an overall test score, a diagnostic test provides each subject with a profile detailing the concepts and skills (often called "attributes") that he/she has mastered. Central to many DCMs is the so-called Q-matrix, an incidence
openaire   +2 more sources

A Population‐Based Study on Childhood Aplastic Anemia—Incidence, Outcomes, and Health‐Related Quality of Life

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Childhood aplastic anemia (AA) is a rare disease, and both the disease itself and its treatment cause significant morbidity. We aimed to determine the contemporary incidence of childhood AA in Finland, to compare the clinical characteristics of AA against inherited bone marrow failure syndromes (IBMFS) and refractory cytopenia of ...
Lauri‐Matti Kulmala, Riitta Niinimäki, Tytti Pokka, Anu Huurre, Liisa Järvelä, Sauli Palmu, Tuuli Pöyhönen, Pauliina Utriainen, Henri Aarnivala   +8 more
wiley   +1 more source