Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Mask-HybridGNet: Graph-based segmentation with emergent anatomical correspondence from pixel-level supervision

Graph-based medical image segmentation represents anatomical structures using boundary graphs, provi...

Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy

Chimeric antigen receptor (CAR) T cell therapies have reshaped treatment for cancers and immune-medi...

HD-TTA: Hypothesis-Driven Test-Time Adaptation for Safer Brain Tumor Segmentation

Standard Test-Time Adaptation (TTA) methods typically treat inference as a blind optimization task, ...

SHAP-Guided CpG Selection with Ensemble Learning for Epigenetic Age Prediction

Abstract Epigenetic biomarkers offer critical insight into biological aging and disease risk, yet mo...

Pushing the Limits of Inverse Lithography with Generative Reinforcement Learning

Inverse lithography (ILT) is critical for modern semiconductor manufacturing but suffers from highly...

Partial Soft-Matching Distance for Neural Representational Comparison with Partial Unit Correspondence

Representational similarity metrics typically force all units to be matched, making them susceptible...

Dual-Channel Attention Guidance for Training-Free Image Editing Control in Diffusion Transformers

Training-free control over editing intensity is a critical requirement for diffusion-based image edi...

RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis

Histopathology, the current gold standard for cancer diagnosis, involves the manual examination of t...

AgriVariant: Variant Effect Prediction using DeepChem-Variant for Precision Breeding in Rice

Predicting functional consequences of genetic variants in crop genes remains a critical bottleneck f...

SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework

Comparative analysis of adaptive immune repertoires at population scale is hampered by two practical...

Deep Agentic Variant Prioritisation for Expert Level Genetic Diagnosis Fast at Scale

Abstract. Genetic diagnosis remains a formidable challenge characterized by a diagnostic odyssey tha...

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 ph...

DELTA: Fortifying Human Biological Resilience with an N=1 Digital Health and Dynamic Biomarker Protocol

Societies are aging rapidly in parallel with the increasingly earlier onset of serious diseases in y...

Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding

Learning from electronic health records (EHRs) time series is challenging due to irregular sam- plin...

Application of Explainable AI in Neuroscience: Enhancing Autism Screening

The main challenges in the life of a child with autism are difficulties in communication, behavior, ...

Clinical validation of automated and multiple manual callosal angle measurement methods in idiopathic normal pressure hydrocephalus

Introduction Idiopathic normal pressure hydrocephalus (iNPH) is a partially reversible neurological ...

Feature-based in-silico model to predict the Mycobacterium tuberculosis bedaquiline phenotype associated with Rv0678 variants

Bedaquiline resistance is emerging globally and threatens the effectiveness of the novel short all-o...

miRXplain: explainable isomiR-aware microRNA target prediction using CLIP-L experiments and hybrid attention transformers

MicroRNAs (miRNAs) are 22 nt long noncoding RNAs that repress genes by base-pairing with complementa...

Genetic variation shapes human mRNA translation and disease risk

Genetic variation can influence protein abundance through translation, yet this regulatory layer rem...

Brain Tumor Classifiers Under Attack: Robustness of ResNet Variants Against Transferable FGSM and PGD Attacks

Adversarial robustness in deep learning models for brain tumor classification remains an underexplor...

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