Results 201 to 210 of about 30,272 (291)

Assessment of the Performance of Siemens Scopio Digital Morphology on Bone Marrow Aspirates in Onco‐Hematology

open access: yesInternational Journal of Laboratory Hematology, EarlyView.
ABSTRACT Objectives Digital morphology (DM) systems assisted by artificial intelligence are increasingly being introduced into hematology laboratories; however, data on their performance in routine clinical practice for bone marrow aspirates (BMA) remain limited.
Gina Zini   +6 more
wiley   +1 more source

Mapping malignant T‐cell states and immune circuits in Sézary syndrome by single‐cell analysis

open access: yesJournal of the European Academy of Dermatology and Venereology, EarlyView.
Peripheral blood single‐cell RNA‐seq from leukaemic CTCL defined three malignant T‐cell programmes: MTC CM, MTC Reg and MTC E/EM, each with distinct features and candidate vulnerabilities. For example, inferred immune circuits highlighted actionable IL‐10/JAK–TYK2–STAT3 signalling, KIR–MHC I inhibitory interactions and myeloid/B‐cell inflammatory and ...
Beth A. Childs   +6 more
wiley   +1 more source

Next-generation CAR-T and CAR-NK cell therapies in hematologic malignancies: engineering for persistence, specificity, and safety. [PDF]

open access: yesDiscov Oncol
Al-Khreisat MJ   +8 more
europepmc   +1 more source

Systemic Therapy for Advanced Hepatocellular Carcinoma in 2026: Current Standard‐of‐Care and Emerging Therapeutic Strategies

open access: yesJournal of Gastroenterology and Hepatology, EarlyView.
ABSTRACT Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, accounting for up to 80% of all cases. Most patients present at an advanced stage and are unsuitable for curative treatments. In the past 5 years, immunotherapy combination has superseded tyrosine kinase inhibitors (TKI) as the standard first‐line therapy for ...
Landon L. Chan   +2 more
wiley   +1 more source

Validation of machine learning based scenario generators

open access: yesJournal of Risk and Insurance, EarlyView.
Abstract Machine learning (ML) methods are becoming increasingly important for designing economic scenario generators for internal models. Validating data‐driven models requires different methods than validating classical, theory‐based models. We discuss two novel aspects of such validation: first, checking the multivariate distribution of risk factors,
Gero Junike, Solveig Flaig, Ralf Werner
wiley   +1 more source

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