Hematology

Deep Learning of Fluorescence Lifetime Imaging Ophthalmoscopy for Type 2 Diabetes Classification

Purpose: To evaluate whether fluorescence lifetime imaging ophthalmoscopy (FLIO) combined with deep learning can detect metabolic signatures for classification of type 2 diabetes mellitus (T2DM). Design: Cross-sectional analysis of participants included AI-READI dataset (version 3) with FLIO imaging and and hemoglobin A1c (HbA1c) measurement. Subjects: 1,783 participants from the AI-READI dataset ...

Geometry-Informed Parameter-Efficient Fine-Tuning of Pre-trained Molecular GNNs for Blood-Brain Barrier Permeability Prediction

Blood-brain barrier permeability (BBBP) prediction is a critical screening task in central nervous system drug discovery, where candidate molecules must be assessed for whether they can cross, or should be prevented from crossing, the blood-brain barrier. However, this task remains challenging because of limited, class-imbalanced datasets and sensitivity to molecular structure. Recent advances in ...

First Investigation of Deep Learning for Intraoperative Gauze Segmentation in Minimally Invasive Abdominal Surgery

Surgical gauze is an essential part of surgical procedures, primarily used for controlling bleeding and absorbing bodily fluids. The post-surgical ret...

Interpretable Machine Learning to Improve Donor-Recipient Matching at Time of Heart Transplantation

BACKGROUND: Machine learning (ML) models have been used to evaluate one-year post-transplant mortality in donor-recipient pairs. Previous modeling uti...

Group Equivariant Diffusion for Anomaly Detection in Computational Cytology

Computational cytology on whole-slide images is challenging because malignant cells are rare, heterogeneous, and annotated slides are scarce. Anomaly ...

An explainable transformer model learning from entire treatment timelines for pan-cancer risk profiling across healthcare systems

Cancer outcomes vary widely between individual patients, each accumulating an irregular record of treatments, diagnoses, measurements, and complicatio...

Comparison of nuisance function construction strategies for double machine learning causal inference in single-cell transcriptomics: shared unsupervised deep learning does not require cross-fitting

Inferring "whether a change in the expression of a given gene causally affects the disease state" from observational single-cell transcriptomic data i...

Deep learning enables cross-species annotation and attribution of ageing states in haematopoietic stem and immune cells

Cross-species transfer is a central bottleneck in single-cell ageing research: mouse studies provide experimentally tractable age labels, whereas huma...

Single-cell foundation models predict durable CAR T response despite imperfect cell annotation

CD19 targeted chimeric antigen receptor (CAR) T cell therapy achieves high initial response rates in B cell acute lymphoblastic leukemia (B ALL), yet ...

GlucoTune: A Unified Framework for Blood Glucose Preprocessing, Forecasting, and Benchmarking in Diabetes

Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing data-driven methods for diabetes management, partic...

Interpretable Peripheral Blood Cell Classification via Vision-Language Concept Bottleneck and Soft Decision Tree

Motivation: Deep learning classifiers for medical image analysis typically function as black boxes, disclosing neither the image features underlying t...

Deep learning representations of human Immune Health for precision immunology

The human immune system is composed of [~]30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Ind...

Machine learning models to improve targeting of blood culture testing

Background Bloodstream infections are a major cause of mortality, yet the primary testing method, blood cultures, have low positivity (<10%) and turna...

Validating Artificial Intelligence Guidance for Ultrasound Acquisition and Remote Interpretation

Background: Venous thromboembolism (VTE), including deep vein thrombosis (DVT), remains a major global health burden. Diagnostic pathways rely on ultr...

Transient Apical Sparing in Hypertensive Heart Disease Explained by Laplace's Law

Background: Apical sparing of left ventricular longitudinal strain (LS) is an echocardiographic clue to cardiac amyloidosis but may also occur in hype...

MAGE: Color-Invariant and Spatial Knowledge Distillation for Gastric Neoplasm Classification

Accurate differentiation between gastric adenoma and carcinoma during endoscopy is critical for clinical decision-making. Yet, this task is highly cha...

Automated Phenotypic Characterization in Rare Hematologic Malignancies Using a Large Language Model-Based Framework

Background. Diagnosis and risk stratification in rare hematologic malignancies such as myeloproliferative neoplasms (MPNs) - polycythemia vera (PV), e...

Multi-omics and network propagation reveal latent innate immune programmes stratifying high-risk thrombotic primary antiphospholipid syndrome

Thrombotic primary antiphospholipid syndrome (thrPAPS) outcomes are associated with thrombosis type (arterial versus venous), recurrence, and antiphos...

DATA-DRIVEN IDENTIFICATION OF SEX DIFFERENCES IN CEREBRAL BLOOD FLOW USING ARTERIAL SPIN LABELLING AND EXPLAINABLE ARTIFICIAL INTELLIGENCE

Purpose: To investigate sex differences in cerebral blood flow through densely parcellated cortical and subcortical regions using explainable artifici...

Hierarchical classification of hematologic malignancies using epigenetic and genetic information

Molecular testing in hematology requires different assays for disease subgroup identification, risk stratification and selection of appropriate treatm...