Prescriptions

Non-verbal Real-time Human-AI Interaction in Constrained Robotic Environments

We study the ongoing debate regarding the statistical fidelity of AI-generated data compared to human-generated data in the context of non-verbal communication using full body motion. Concretely, we ask if contemporary generative models move beyond surface mimicry to participate in the silent, but expressive dialogue of body language. We tackle this question by introducing the first framework that...

Fake It Right: Injecting Anatomical Logic into Synthetic Supervised Pre-training for Medical Segmentation

Vision Transformers (ViTs) excel in 3D medical segmentation but require massive annotated datasets. While Self-Supervised Learning (SSL) mitigates this using unlabeled data, it still faces strict privacy and logistical barriers. Formula-Driven Supervised Learning (FDSL) offers a privacy-preserving alternative by pre-training on synthetic mathematical primitives. However, a critical semantic gap li...

See, Act, Adapt: Active Perception for Unsupervised Cross-Domain Visual Adaptation via Personalized VLM-Guided Agent

Pre-trained perception models excel in generic image domains but degrade significantly in novel environments like indoor scenes. The conventional reme...

Inferring Chronic Treatment Onset from ePrescription Data: A Renewal Process Approach

Longitudinal electronic health record (EHR) data are often left-censored, making diagnosis records incomplete and unreliable for determining disease o...

Permutation-calibrated stability discovery under ???? >> ????: A leak-controlled Machine Learning framework identifies candidate proteomics panels in antiseizure medication-related side effects

We investigated whether the plasma proteome distinguishes people with epilepsy who report central nervous system (CNS) side effects from antiseizure m...

AI predicted TCR-pMHC structures differentiate immune interactions

The T Cell Receptor (TCR) is a highly variable component of the T cell immune response that recognizes unique epitopes presented on MHC molecules (pMH...

A Framework for Autonomous AI-Driven Drug Discovery

The exponential increase in biomedical data offers unprecedented opportunities for drug discovery, yet overwhelms traditional data analysis methods, l...

Interactive Medical-SAM2 GUI: A Napari-based semi-automatic annotation tool for medical images

Interactive Medical-SAM2 GUI is an open-source desktop application for semi-automatic annotation of 2D and 3D medical images. Built on the Napari mult...

Learning Disease-Sensitive Latent Interaction Graphs From Noisy Cardiac Flow Measurements

Cardiac blood flow patterns contain rich information about disease severity and clinical interventions, yet current imaging and computational methods ...

Reliable XAI Explanations in Sudden Cardiac Death Prediction for Chagas Cardiomyopathy

Sudden cardiac death (SCD) is unpredictable, and its prediction in Chagas cardiomyopathy (CC) remains a significant challenge, especially in patients ...

Using machine learning to automate the analysis of an olfactory habituation-dishabituation task in mice

Introduction Improving the efficiency and accuracy of annotation and extraction of performance data from mouse behavioural tasks will improve both the...

Biomedical Large Language Models and Prompt Engineering for Causality Assessment of Individual Case Safety Reports in Pharmacovigilance

Background: Biomedical Large Language Models (LLMs) combined with prompt engineering offer domain-specific reasoning, yet their application to individ...

Benchmarking Transfer Learning for Dense Breast Tissue Segmentation on Small Mammogram Datasets

Dense breast tissue diminishes the sensitivity of mammographic screening and is a key cancer risk factor, which motivates accurate segmentation under ...

How Agent Role Structure Alters Operating Characteristics of Large Language Model Clinical Classifiers: A Comparative Study of Specialist and Deliberative Multi-Agent Protocols

Large language models (LLMs) are increasingly evaluated for structured clinical decision support tasks, often using multi-agent architectures. Prior w...

PyVision-RL: Forging Open Agentic Vision Models via RL

Reinforcement learning for agentic multimodal models often suffers from interaction collapse, where models learn to reduce tool usage and multi-turn r...

CellAwareGNN: Single-Cell Enhanced Knowledge Graph Foundation Model for Drug Indication Prediction

Graph foundation models have emerged as powerful tools for drug repurposing by enabling the prediction of novel drug-disease indications from large bi...

Survival risk heterogeneity among patients with NSCLC receiving nivolumab visualized by risk scores generated from deep learning method DeepSurv using tumor gene mutations

Immunotherapy with immune checkpoint inhibitors and immunotherapy combined with chemotherapy have represented promising treatments for NSCLC patients ...

Interactions that reshape the interfaces of the interacting parties

Polynomial functors model systems with interfaces: each polynomial specifies the outputs a system can produce and, for each output, the inputs it acce...

LERD: Latent Event-Relational Dynamics for Neurodegenerative Classification

Alzheimer's disease (AD) alters brain electrophysiology and disrupts multichannel EEG dynamics, making accurate and clinically useful EEG-based diagno...

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

Abstract. Genetic diagnosis remains a formidable challenge characterized by a diagnostic odyssey that spans years, with over half of rare disease pati...