Hematology

Lymphoma

Latest AI and machine learning research in lymphoma for healthcare professionals.

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Quantum Convolutional HLA Immunogenic Peptide Prediction (Q-CHIPP): Next-Generation Neoantigen Prediction with Quantum Neural Networks

The immune system is an intricately evolved series of cellular and protein-protein interactions, whi...

Design of peptides with non-canonical amino acids using flow matching

The canonical vocabulary of twenty amino acids limits the chemical space available to proteins and p...

Integration of steady-state diffusion MRI with Neural Posterior Estimation (NPE) for post-mortem investigations

Post-mortem diffusion MRI plays a key role in investigative pipelines to characterise tissue microst...

Decoding Helicobacter pylori Resistance: Machine Learning–Enhanced Prediction of Antibiotic Susceptibility using Whole-Genome Sequencing

Helicobacter pylori is a significant risk factor for gastric cancer, peptic ulcers, and MALT lymphom...

Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic Data

Alzheimer’s disease and related dementias (ADRD) involve overlapping neurodegenerative and vascular ...

Regularized Single-cell Imaging Enables Generalizable AI models for Stain-free Cell Viability Screening

Cell viability assays are essential tools in biomedical research and drug development. Artificial in...

Quantum Deep Learning Pipeline for Next Generation Network Biology

Module discovery in omics networks is central to interpretation. Classical pipelines capture broad c...

Automatic Classification of Circulating Blood Cell Clusters based on Multi-channel Flow Cytometry Imaging

Circulating blood cell clusters (CCCs) containing red blood cells (RBCs), white blood cells (WBCs), ...

Prediction of lncRNA-protein interacting pairs using LLM embeddings based on evolutionary information

Interactions of long non-coding RNAs (lncRNAs) with proteins is responsible for numerous cellular pr...

Disentangling Superpositions: Interpretable Brain Encoding Model with Sparse Concept Atoms

Encoding models based on word embeddings or artificial neural network (ANN) features reliably predic...

scCotag: Diagonal integration of single-cell multi-omics data via prior-informed co-optimal transport and regularized barycentric mapping

Recent advances in high-throughput single-cell technologies have enabled characterization of cellula...

Multimodal Deep Learning Model to Estimate CT-based Body Composition Measures Using Chest radiographs and Clinical Data

Body composition metrics such as visceral fat volume, subcutaneous fat volume and skeletal muscle vo...

Fusing Data from CT Deep Learning, CT Radiomics and Peripheral Blood Immune profiles to Diagnose Lung Cancer in Symptomatic Patients

Lung cancer is the leading cause of cancer-related deaths. Diagnosis at late stages is common due to...

Development of a Claims-Based Computable Phenotype for Ulcerative Colitis Flares

Several conditions exist that do not have their own unique diagnosis code in widely-used clinical te...

Multi-resolution vision transformer model for skin cancer subtype classification using histopathology slides

Digital pathology has significantly advanced cancer diagnosis by enabling high-resolution visualisat...

Exploring multidrug resistance patterns in community-acquired E. coli urinary tract infections with machine learning

While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacte...

Leveraging functional annotations to map rare variants associated with Alzheimer’s disease with gruyere

The increasing availability of whole-genome sequencing (WGS) has begun to elucidate the contribution...

Peritoneal Metastasis Prediction in Gastric Cancer: A Machine Learning Approach

Evaluate the predictive efficacy of six machine learning (ML) algorithms in identifying peritoneal m...

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