Leukemia

Likelihood-Free Parameter Inference for Spatiotemporal Stochastic Biological Models using Neural Posterior Estimation

Cell migration is a key biological process underlying wound healing, tissue development, and cancer metastasis, yet calibrating mathematical models of migration to experimental data remains a major challenge. Scratch and barrier assays are widely used to study collective cell spreading, and agent-based random walk models provide a natural stochastic description of these experiments. However, param...

Revisiting the Role of Foundation Models in Cell-Level Histopathological Image Analysis under Small-Patch Constraints -- Effects of Training Data Scale and Blur Perturbations on CNNs and Vision Transformers

Background and objective: Cell-level pathological image analysis requires working with extremely small image patches (40x40 pixels), far below standard ImageNet resolutions. It remains unclear whether modern deep learning architectures and foundation models can learn robust and scalable representations under this constraint. We systematically evaluated architectural suitability and data-scale effe...

Transcriptomic profiling of mouse mammary tumors enables prognostic and predictive biomarker discovery for human breast cancers

The development and validation of prognostic and predictive biomarkers in breast cancer is limited by the availability of well-annotated datasets link...

Temporal dynamics of radiotherapy and chemotherapy response in lower-grade gliomas using causal machine learning

Lower-grade gliomas (World Health Organization [WHO] grades 2-3) exhibit variable treatment responses, yet clinical decisions remain guided by populat...

Can Machine Learning Algorithms use Contextual Factors to Detect Unwarranted Clinical Variation from Electronic Health Record Encounter Data during the Treatment of Children Diagnosed with Acute Viral Pharyngitis

Rationale, Aims and Objectives: Unwarranted clinical variation (UCV) in patient care often arises from contextual factors and contributes to increased...

Robust White Blood Cell Classification with Stain-Normalized Decoupled Learning and Ensembling

White blood cell (WBC) classification is fundamental for hematology applications such as infection assessment, leukemia screening, and treatment monit...

AMLRIS: Alignment-aware Masked Learning for Referring Image Segmentation

Referring Image Segmentation (RIS) aims to segment an object in an image identified by a natural language expression. The paper introduces Alignment-A...

CellAwareGNN: Single-Cell Enhanced Knowledge Graph Foundation Model for Drug Indication Prediction

Graph foundation models have emerged as powerful tools for drug repurposing by enabling the prediction of novel drug-disease indications from large bi...

Survival risk heterogeneity among patients with NSCLC receiving nivolumab visualized by risk scores generated from deep learning method DeepSurv using tumor gene mutations

Immunotherapy with immune checkpoint inhibitors and immunotherapy combined with chemotherapy have represented promising treatments for NSCLC patients ...

Accelerated sampling of protein dynamics using BioEmu augmented molecular simulation

We introduce a workflow that integrates BioEmu-generated conformational ensemble with physics-based molecular simulations and Markov State Models to s...

Development and cross-tissue validation of a methylation profile score for the cortisol response to stress

Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and physical health. Animal studies indicate that DNA me...

A visualization framework for cell division activity and orientation in pre-anthesis ovaries of Prunus species

Fruit size and shape, which influence horticultural quality, are determined by the number and the size of the cells in the local region. In fruit tree...

Systematic Evaluation of Transfer Learning Strategies for Clinical Chemotherapy Response Prediction

Accurately predicting chemotherapy response remains a major challenge in precision oncology. Although machine-learning models based on tumour omics da...

Named Entity Recognition for Payment Data Using NLP

Named Entity Recognition (NER) has emerged as a critical component in automating financial transaction processing, particularly in extracting structur...

A single-cell atlas and aging clock define biological age and risk-associated stem cell states in human hematopoiesis

Aging of hematopoietic stem and progenitor cells (HSPCs) impairs regenerative capacity and predisposes to hematological diseases. Here, we constructed...

A custom phenotypic profile for Fanconi anemia: Addressing gaps in existing disease annotations

Fanconi anemia (FA) is a rare genetic disorder of impaired DNA repair characterized by progressive bone marrow failure, congenital malformations, and ...

ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, many-forms'...

Autoregressive forecasting of future single-cell state transitions

Existing methods for dynamic analysis of static single-cell RNA-sequencing data can reconstruct temporal structures covered by observed cells, but can...

Multimodal Machine Learning Reveals the Genomic and Proteomic Architecture of Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) affects over 30 million people and lacks disease-modifying therapies. Although genomic-led drug...

Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference.

Single-cell expression quantitative trait loci (eQTL) studies hold promise for linking genetic variants to changes in gene expression in individual ce...