Prescriptions

AIM-DDI: A Model-Agnostic Multimodal Integration Module for Drug-Drug Interaction Prediction

Drug-drug interaction (DDI) prediction is a critical task in computational biomedicine, as adverse interactions between co-administered drugs can cause severe side effects and clinical risks. A key challenge is unseen-drug generalization, where interactions must be predicted for drugs not observed during training. Although multimodal DDI models exploit diverse drug-related information, their fusio...

RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation

Inpatient medication recommendation requires clinicians to repeatedly select specific medications, doses, and routes as a patient's condition evolves. Existing benchmarks formulate this task as admission-level prediction over coarse drug codes with multi-hot diagnostic and procedure code inputs, failing to capture the per-timepoint, information-rich nature of real prescribing. We propose RxEval, a...

NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces

Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including...

Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model

Sepsis management in the ICU requires sequential treatment decisions under rapidly evolving patient physiology. Although large language models (LLMs) ...

SceneParser: Hierarchical Scene Parsing for Visual Semantics Understanding

General scene perception has progressed from object recognition toward open-vocabulary grounding, part localization, and affordance prediction. Yet th...

A transformer model explaining mechanisms of drug therapeutic and adverse effects

Understanding which disease genes are altered by a drug can provide insight into the biology of effect, help us understand adverse drug effects, and s...

PresentAgent-2: Towards Generalist Multimodal Presentation Agents

Presentation generation is moving beyond static slide creation toward end-to-end presentation video generation with research grounding, multimodal med...

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone

Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language mod...

Development of a Deep Learning Model Integrating CT Images and Blood Data for the Diagnosis of Acute Cholecystitis

Purpose: In this study, we aimed to develop and evaluate an artificial intelligence-based diagnostic model for the diagnosis of acute cholecystitis (A...

Cadence: A Benchmark Evaluation of the Narrative Velocity Framework for Next Clinical Event Prediction in MIMIC-IV

Objective: How structured clinical features and cluster-semantic embeddings interact under self-distillation in EHR prediction models is unknown. Exis...

SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation

Video generation has advanced rapidly, producing photorealistic videos from text or image prompts. Meanwhile, film production and social robotics incr...

Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition

Recent research work on fashion outfit generation focuses on promoting visual consistency of garments by leveraging key information from reference ima...

AdaptSplat: Adapting Vision Foundation Models for Feed-Forward 3D Gaussian Splatting

This work explores a simple yet powerful lightweight adapter design for feed-forward 3D Gaussian Splatting (3DGS). Existing methods typically apply co...

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs

Biomedical knowledge graphs underwrite drug repurposing and clinical decision support, yet the upstream ontologies they depend on update on independen...

SwiftI2V: Efficient High-Resolution Image-to-Video Generation via Conditional Segment-wise Generation

High-resolution image-to-video (I2V) generation aims to synthesize realistic temporal dynamics while preserving fine-grained appearance details of the...

BRICKS: Compositional Neural Markov Kernels for Zero-Shot Radiation-Matter Simulation

We introduce a new strategy for compositional neural surrogates for radiation-matter interactions, a key task spanning domains from particle physics t...

ChatIBD: design, safeguards, and early international use of a guideline-grounded generative AI tool for inflammatory bowel disease (IBD) professionals

Objectives To describe the design, operational safeguards, and early use of ChatIBD, a specialty-specific generative AI platform for inflammatory bowe...

Artificial Intelligence Driven Support and Self Care Competence as Determinants of Medication Adherence in Diabetes Care, A Cross-sectional Nigerian Study

Medication adherence among patients with diabetes remains suboptimal in low and middle income countries, including Nigeria. Emerging digital health in...

Classification of Smartphone Interaction Using Multimodal Physiological Signals with a Brain-Body Spatio-Temporal Transformer

Distinct smartphone interaction behaviors, like short-form video scrolling and mobile gaming, elicit qualitatively different cognitive and physiologic...

SmartAlert: Integrating Machine Learning and Alert Triggers into Live Electronic Medical Record Systems, Targeting Low-Yield Inpatient Lab Tests

This study explores integrating machine learning into electronic medical record systems to predict stability of inpatient lab tests. A 'SmartAlert' sy...