803. Emerging Tools, Techniques, and Artificial Intelligence in Hematology: Poster II

A multi institutional machine learning score that predicts bacteremia and gram class at blood culture initiation

Validation of the artificial intelligence prediction of acute leukemia tool in a Latin American retrospective cohort

TP53 mutational spectrum and fitness landscape in myeloid neoplasia

Performance of different large language models LLMs as decision support tools across various hematologic malignancies

Machine learning using bayesian networks to predict response in patients with newly diagnosed Acute Myeloid Leukemia

Alphagenome enabled analysis of non coding regulatory variants underlying rhd expression

Application of hi c sequencing to detect cryptic and novel structural aberrations in lymphoid neoplasms

Image based classification of lymphocyte subsets from routine blood smears reveals distinct immune dynamics after CAR T infusion

Whole genome sequencing WGS based circulating tumor DNA ctDNA monitoring in diffuse large B cell lymphoma DLBCL

AI based secure and privacy preserving synthetic data generation platform in transfusion dependent β thalassemia applied to the Webthal® dataset

Development and validation of synthetic data generation over a federated learning computing framework to accelerate innovation and boost personalized medicine in hematological diseases

Xgboost model using diagnostic CBC to predict early mortality in newly diagnosed AML patients

Redefining the myeloid disease continuum Machine learning–based development and validation of an integrated multimodal classification of myeloid neoplasms

Delta oscillation enhancement and alpha oscillation attenuation as electroencephalogram biomarkers of CNS demyelination in patients with hematologic malignancies

A predictive framework leveraging integration site profiling to stratify CAR T response in Relapsed Refractory multiple myeloma

Interpretable deep learning predicts polycythemia vera and identifies novel genomic associations

Distinct morphological features of malignant cells in large B cell lymphoma identified by soft segmentation in imaging based spatial proteomics

Early identification of patients likely to benefit from paroxysmal nocturnal hemoglobinuria workup using machine learning on large scale real world data

Using a medically trained LLM based end to end system in automating patient eligibility screening across a health system for A phase 3 study evaluating the safety of givinostat in patients with polycythemia vera

The clinical utility of COMET™ sequential immunofluorescence in lymphoma tissue diagnostics Next generation diagnosis

Uncovering bispecific antibody mechanisms via 3D superresolution imaging of T cell tumor cell membrane contacts

Comprehensive and rapid detection of genomic alterations in pediatric leukemias using whole genome sequencing with adaptive sampling

A novel method for molecular subtyping diffuse large B cell lymphoma using whole exome sequencing

Toward precision pathology Deep learning supported fibrosis grading augments performance of international hematopathologists in a large real world cohort

DNA sequencing outperforms RNA sequencing for comprehensive fusion detection in lymphoma diagnostics

Developing a simplified ex vivo culturing protocol for personalized myeloma treatment in rural areas

Code red Codigo Rojo Multimodal generative AI for specialized hematology education