Prescriptions

Pan-Pharmacological Drug-Target Interaction Prediction with 3D-Informed Protein Encoding at Scale

Accurate prediction of drug-target binding affinity across multiple pharmacological endpoints remains challenging, as most deep learning methodologies focus on a single metric and face a trade-off between incorporating structural information and computational throughput. Here we present OmniBind, a multitask framework that resolves both constraints by encoding protein tertiary structures as discre...

PHENOCAUZ: Linking Human Symptoms, Drug Side Effects and Efficacy to Their Molecular Causes Using Mendelian Disease Biology

Human diseases and adverse drug reactions are ultimately recognized through clinical symptoms, yet the molecular determinants of most symptoms remain unknown. To address this key issue, we present PHENOCAUZ, a computational framework that links symptoms to their causative proteins by integrating Mendelian phenotype - gene relationships with molecular features of proteins. Starting from symptom ann...

Streamlined Open-Vocabulary Human-Object Interaction Detection

Open-vocabulary human-object interaction (HOI) detection aims to localize and recognize all human-object interactions in an image, including those uns...

faers: A High-Fidelity Framework and R/Bioconductor Package for Precision Adverse Event Surveillance

Background: The FDA Adverse Event Reporting System (FAERS) is a critical pillar of post-marketing pharmacovigilance; however, its utility is constrain...

When Identities Collapse: A Stress-Test Benchmark for Multi-Subject Personalization

Subject-driven text-to-image diffusion models have achieved remarkable success in preserving single identities, yet their ability to compose multiple ...

ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks

Safety-critical domains like healthcare rely on deep neural networks (DNNs) for prediction, yet DNNs remain vulnerable to evasion attacks. Anomaly det...

Improving Risk Stratification in Hypertrophic Cardiomyopathy: A Novel Score Combining Echocardiography, Clinical, and Medication Data

Hypertrophic cardiomyopathy (HCM) requires accurate risk stratification to inform decisions regarding ICD therapy and follow-up management. Current es...

DuSCN-FusionNet: An Interpretable Dual-Channel Structural Covariance Fusion Framework for ADHD Classification Using Structural MRI

Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental condition; however, its neurobiological diagnosis remains cha...

Interpretable long-term traffic modelling on national road networks using theory-informed deep learning

Long-term traffic modelling is fundamental to transport planning, but existing approaches often trade off interpretability, transferability, and predi...

OPTIMIS: Optimizing Personalized Therapies through Integrated Multiscale Intelligent Simulation

Controlling complex biological systems across multiple scales remains a major challenge in computational medicine, because whole-body disease behavior...

Predicting Unseen Gene Perturbation Response Using Graph Neural Networks with Biological Priors

Predicting transcriptional responses to genetic perturbations is a central challenge in functional genomics. CRISPR Perturb-seq experiments measure ge...

Associative Memory using Attribute-Specific Neuron Groups-2: Learning and Sequential Associative Recall between Cue Neurons for different Cue Balls

This paper introduces a neural network model that learns multiple attributes as images and performs associated, sequential recall of the learned memor...

Knowledge-Guided Failure Prediction: Detecting When Object Detectors Miss Safety-Critical Objects

Object detectors deployed in safety-critical environments can fail silently, e.g. missing pedestrians, workers, or other safety-critical objects witho...

VIOLIN: A modular framework for scalable reconciliation of heterogeneous interaction graphs

Automated extraction of molecular interactions from scientific literature has outpaced the development of systematic methods for integrating this info...

A^3: Towards Advertising Aesthetic Assessment

Advertising images significantly impact commercial conversion rates and brand equity, yet current evaluation methods rely on subjective judgments, lac...

ViHOI: Human-Object Interaction Synthesis with Visual Priors

Generating realistic and physically plausible 3D Human-Object Interactions (HOI) remains a key challenge in motion generation. One primary reason is t...

Revisiting Weakly-Supervised Video Scene Graph Generation via Pair Affinity Learning

Weakly-supervised video scene graph generation (WS-VSGG) aims to parse video content into structured relational triplets without bounding box annotati...

Generalized Hand-Object Pose Estimation with Occlusion Awareness

Generalized 3D hand-object pose estimation from a single RGB image remains challenging due to the large variations in object appearances and interacti...

Computational Fluid Particle Dynamics-Informed Machine Learning Prototype for a User-Centered Smart Inhaler Enabling Uniform Drug Delivery to Small Airways

Small airways are the primary sites of airflow obstruction in chronic obstructive pulmonary disease. Effective delivery of aerosolized drug particles ...

AndroTMem: From Interaction Trajectories to Anchored Memory in Long-Horizon GUI Agents

Long-horizon GUI agents are a key step toward real-world deployment, yet effective interaction memory under prevailing paradigms remains under-explore...