AI Medical Compendium Journal:
Blood advances

Showing 1 to 10 of 13 articles

Soluble interleukin-2 receptor is a sensitive diagnostic test in adult HLH.

Blood advances
Serum soluble interleukin-2 receptor (sIL-2r) is an important disease marker in hemophagocytic lymphohistiocytosis (HLH), but there are no published data on its diagnostic value in adults. We conducted a single-center retrospective study of 78 consec...

Serologic characterization of anti-protamine/heparin and anti-PF4/heparin antibodies.

Blood advances
Anti-protamine (PRT)/heparin antibodies are a newly described class of heparin-dependent antibodies occurring in patients exposed to PRT and heparin during cardiac surgery. To understand the biologic significance of anti-PRT/heparin antibodies, we de...

Cardiac and renal complications of carfilzomib in patients with multiple myeloma.

Blood advances
Clinical trials with carfilzomib have indicated a low but reproducible incidence of cardiovascular and renal toxicities. Among 60 consecutive myeloma patients treated with carfilzomib-based regimens who were thoroughly evaluated for cardiovascular ri...

Novel machine learning technique further clarifies unrelated donor selection to optimize transplantation outcomes.

Blood advances
We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell transplantation (HCT) recipients using a novel machine learning approach, the Nonparametric Failure Time Bayesian Additive Regression Trees (NFT BART). N...

Artificial intelligence enabled interpretation of ECG images to predict hematopoietic cell transplantation toxicity.

Blood advances
Artificial intelligence (AI)-enabled interpretation of electrocardiogram (ECG) images (AI-ECGs) can identify patterns predictive of future adverse cardiac events. We hypothesized that such an approach would provide prognostic information for the risk...

Machine learning natural language processing for identifying venous thromboembolism: systematic review and meta-analysis.

Blood advances
Venous thromboembolism (VTE) is a leading cause of preventable in-hospital mortality. Monitoring VTE cases is limited by the challenges of manual medical record review and diagnosis code interpretation. Natural language processing (NLP) can automate ...

Machine learning to optimize automated RH genotyping using whole-exome sequencing data.

Blood advances
Rh phenotype matching reduces but does not eliminate alloimmunization in patients with sickle cell disease (SCD) due to RH genetic diversity that is not distinguishable by serological typing. RH genotype matching can potentially mitigate Rh alloimmun...

Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears.

Blood advances
The detection of genetic aberrations is crucial for early therapy decisions in acute myeloid leukemia (AML) and recommended for all patients. Because genetic testing is expensive and time consuming, a need remains for cost-effective, fast, and broadl...