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Clinical Trials & Observations
Journal: Blood
Blood (2025) 146 (19): 2275–2276.
Published: 2025
Journal Articles
Journal Articles
Journal Articles
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Definitions of AI subtypes and examples of ML and DL applications in hematology. Various definitions of AI subtypes are illustrated and examples of ML and DL techniques in the field of hematology are shown.
Published: 2025
Figure 1. Definitions of AI subtypes and examples of ML and DL applications in hematology. Various definitions of AI subtypes are illustrated and examples of ML and DL techniques in the field of hematology are shown. More about this image found in Definitions of AI subtypes and examples of ML and DL applications in hemato...
Images
Multimodal ML framework for integrative analysis in hematology. The integration of heterogeneous data types (clinical variables, radiologic imaging, histopathology, and high-throughput sequencing) using a multimodal ML pipeline is depicted. After preprocessing and data fusion, ML models are trained to capture relationships across modalities. These models support key clinical applications including the classification of hematologic malignancies (eg, lymphoma subtyping), prediction of clinical outcomes (eg, survival or progression after CAR T-cell therapy), discovery of prognostic and predictive biomarkers, and development of digital twins to simulate individualized treatment responses. Icons in this figure were generated using ChatGPT (OpenAI).
Published: 2025
Figure 2. Multimodal ML framework for integrative analysis in hematology. The integration of heterogeneous data types (clinical variables, radiologic imaging, histopathology, and high-throughput sequencing) using a multimodal ML pipeline is depicted. After preprocessing and data fusion, ML model... More about this image found in Multimodal ML framework for integrative analysis in hematology. The integr...
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Application of AI in diagnostic hematology. The use of AI technologies in various aspects of diagnostic hematology, including cell type identification, detection of dysplasia, chromosomal analysis, and disease classification are highlighted. AI-driven techniques such as automated image/data processing and others are shown to improve diagnostic accuracy and enable minimal residual disease detection.
Published: 2025
Figure 3. Application of AI in diagnostic hematology. The use of AI technologies in various aspects of diagnostic hematology, including cell type identification, detection of dysplasia, chromosomal analysis, and disease classification are highlighted. AI-driven techniques such as automated image... More about this image found in Application of AI in diagnostic hematology. The use of AI technologies in ...
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Application of AI in genomic/precision medicine. Schematic overview of AI integration in precision medicine. Patient-derived clinical data and biospecimens undergo multiomic profiling and sequencing analysis. These heterogeneous datasets are processed using AI algorithms to extract diagnostic (eg, identification of inherited and pathogenic variants), prognostic (eg, survival and therapy response prediction), and generative insights (eg, protein structure modeling and digital twin simulations), enabling advanced biomedical decision-making.
Published: 2025
Figure 4. Application of AI in genomic/precision medicine. Schematic overview of AI integration in precision medicine. Patient-derived clinical data and biospecimens undergo multiomic profiling and sequencing analysis. These heterogeneous datasets are processed using AI algorithms to extract dia... More about this image found in Application of AI in genomic/precision medicine. Schematic overview of AI ...
Images
GWAS results from the meta-analysis on VTE recurrence. (A) Manhattan plot: horizontal red line represents the genome-wide threshold (P < 5 × 10−8). One significant locus is annotated on this plot with its nearest gene. (B) Quantile-quantile plot.
Published: 2025
Figure 1. GWAS results from the meta-analysis on VTE recurrence. (A) Manhattan plot: horizontal red line represents the genome-wide threshold ( P < 5 × 10 −8 ). One significant locus is annotated on this plot with its nearest gene. (B) Quantile-quantile plot. More about this image found in GWAS results from the meta-analysis on VTE recurrence. (A) Manhattan plot:...
Images
Association of GPR149;MME genome-wide significant locus (rs34097149-C). (A) Regional association plot around the SNP. (B) Forest plot representing the HR for VTE recurrence for all studies. (C) Forest plot representing the HR for VTE recurrence of the SNP effects across the subgroups and in the main analysis. Chr3, chromosome 3; EAF, effect allele frequency; INFO, imputation quality score; NREC, number of VTE recurrences.
Published: 2025
Figure 2. Association of GPR149;MME genome-wide significant locus (rs34097149-C). (A) Regional association plot around the SNP. (B) Forest plot representing the HR for VTE recurrence for all studies. (C) Forest plot representing the HR for VTE recurrence of the SNP effects across the subgroups... More about this image found in Association of GPR149;MME genome-wide significant locus (rs34097149-C). ...