Latest AI and machine learning research in myeloma for healthcare professionals.
Binary data factorization is common, but real-valued methods ignore discreteness and yield hard-to-interpret factors. Boolean Matrix Factorization (BooMF) instead decomposes a binary matrix into two lower-rank binary matrices via logical AND and OR, expressing the data as a Boolean disjunction of interpretable patterns. In cancer genomics, BooMF can reveal coordinated feature changes that may driv...
Binary data factorization is common, but real-valued methods ignore discreteness and yield hard-to-interpret factors. Boolean Matrix Factorization (BooMF) instead decomposes a binary matrix into two lower-rank binary matrices via logical AND and OR, expressing the data as a Boolean disjunction of interpretable patterns. In cancer genomics, BooMF can reveal coordinated feature changes that may driv...
Routine laboratory panels drawn during cancer treatment constitute longitudinal physiological recordings of organ function, yet their temporal structu...
Today, advancements in our understanding of cancer biology are increasingly attributed to large-scale clinical-molecular datasets. The case in point f...
Background: Anemia is an established marker of cardiovascular disease severity and risk which leads to elevations in resting myocardial blood flow (MB...
This paper examines what it means for a medical AI system to be right by grounding the question in a specific clinical context: the automatic classifi...
Multiple myeloma (MM) orchestrates immune evasion by subverting natural killer (NK) cell function. CD48, one of the most abundant NK-ligands on MM cel...
Translating transcriptomic data into therapeutic hypotheses remains fragmented and labor-intensive. Here we present ConvergeCELL, a platform combining...
Adverse drug effects remain a major barrier to safe and effective cancer therapy, underscoring the need for tools that predict treatment-related toxic...
This paper introduces StructDiff, a generative framework based on a single-scale diffusion model for single-image generation. Single-image generation ...
Multimodal variational autoencoders (VAEs) have emerged as a powerful framework for survival risk modeling in multiple myeloma by integrating heteroge...
Background: Advances in medicine depend on analyzing large and complex data sources, but discovery is partly constrained by the limited time and domai...
Background: Anemia is nearly ubiquitous in hospitalized patients with congestive heart failure (CHF), yet little data informs the decision to transfus...
Background: Large language models (LLMs) show promise for clinical decision support, yet most validation studies evaluate single models, leaving quest...
Fanconi anemia (FA) is a rare genetic disorder of impaired DNA repair characterized by progressive bone marrow failure, congenital malformations, and ...
Childhood anemia remains a major public health challenge in Nepal and is associated with impaired growth, cognition, and increased morbidity. Using Wo...
Abstract: Anemia, particularly iron-deficiency anemia, is a critical global health concern, with a high prevalence among children under six years of a...
B-cell maturation antigen (BCMA) shedding by {gamma}-secretase generates soluble BCMA (sBCMA) , which diminishes membrane antigen density, and limits ...
The link between individual metals and gestational anemia has been established, but the impact of metal mixtures and the mediating role of renal funct...