Pancreatic Diseases

Assessing Pancreatic Ductal Adenocarcinoma Vascular Invasion: the PDACVI Benchmark

Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate assessment of vascular invasion (VI), i.e., tumor extension into adjacent critical vessels. Despite its importance for preoperative staging and surgical planning, computational VI assessment remains underexplored. Two major challenges are the lack of p...

Autonomous multimodal agents enable transparent, spatiotemporal reconstruction of immune dynamics in pancreatic cancer progression

Pancreatic cancer progression is orchestrated by dynamic shifts in immune and stromal cellular ecosystems, yet the temporal and spatial principles governing these transitions remain poorly understood. Here, we present an agentic computational pathology framework that leverages large language models to orchestrate modular biomarker inference and spatiotemporal reasoning directly from routine H&E hi...

PanGuide3D: Cohort-Robust Pancreas Tumor Segmentation via Probabilistic Pancreas Conditioning and a Transformer Bottleneck

Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often sma...

SCOPE: Integrating Organoid Screening and Clinical Variables Through Machine Learning for Cancer Trial Outcome Prediction

BackgroundPredicting whether a treatment will demonstrate meaningful clinical benefit before committing to a large-scale trial remains a major unmet n...

TwinTrack: Post-hoc Multi-Rater Calibration for Medical Image Segmentation

Pancreatic ductal adenocarcinoma (PDAC) segmentation on contrast-enhanced CT is inherently ambiguous: inter-rater disagreement among experts reflects ...

A Machine Learning Based Causal Interface for Time-Varying Environmental Predictors of Substance Use Initiation in the ABCD Study

Background: The Adolescent Brain Cognitive Development (ABCD) Study provides rich longitudinal data on environmental, genetic, and behavioral factors ...

Virtual Spectral Decomposition with Dendritic Tile Selection: An Explainable AI Framework for Multimodal Tissue Composition Analysis and Immune Phenotyping Across Pancreatic, Lung, and Breast Cancer

Background: Current deep learning models in computational pathology, radiology, and digital pathology produce opaque predictions that lack the explain...

TELF: An End-to-End Temporal Encoder with Late Fusion for Interpretable Disease Risk Prediction from Longitudinal Real-World Data

Deep learning models utilizing longitudinal healthcare data have significantly advanced epidemiological research. However, contemporary transformer-ba...

Altered EEG markers of reward learning during abstinence in alcohol dependence: a probabilistic reversal learning study

Maladaptive reward learning and decision-making circuity are key factors in the onset and progression of alcohol use disorder and have therefore emerg...

Automated Extraction of Cancer Registry Data from Pathology Reports: Comparing LLM-Based and Ontology-Driven NLP Platforms

Cancer data standardization requires converting unstructured pathology reports into structured registry variables, a mostly manual and resource-intens...

pertTF: context-aware AI modeling for genome-scale and cross-system perturbation prediction

Predicting genetic perturbation responses at a single-cell level is central to building models for cell state and disease. However, existing approache...

Consumption of Reinforcing Solutions Engages Dynamic Activityof the Prelimbic Cortical Outputs

The medial prefrontal cortex integrates information about salience and valence of stimuli, including rewarding solutions like alcohol and sucrose, and...

A Lightweight Multi-Cancer Tumor Localization Framework for Deployable Digital Pathology

Accurate localization of tumor regions from hematoxylin and eosin-stained whole-slide images is fundamental for translational research including spati...

Structured Schemas for LLM-Modeler Collaboration in Quantitative Systems Pharmacology Model Calibration

Quantitative systems pharmacology (QSP) models require calibration data from published literature, yet manual curation produces inconsistent documenta...

Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer

Resistance to systemic therapy is a major unmet challenge in pancreatic cancer. To identify potential mechanisms of resistance, we developed a novel 3...

Enhanced Insights into Alcohol Use Disorder from Lifestyle, Background, and Family History in a Large-Scale Machine Learning Study

Alcohol Use Disorder (AUD) is a multifactorial condition with severe individual and societal impacts. Extending our 2024 study, this work examines lif...

Conversational Artificial Intelligence Agents-Enabled Dissection of RTK-RAS and MAPK Pathway Dependencies in Gemcitabine-Treated Pancreatic Ductal Adenocarcinoma (PDAC)

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by profound molecular heterogeneity and inconsistent responses to ge...

Cognition, Lifestyles, and Environments: Quantifying the Roles of Body Physiology and the Brain

Lifestyle and environmental factors such as diet, physical activity, residential greenspace exposure, alcohol consumption, and sleep are increasingly ...

Cannabis Use Documentation within the Electronic Health Record: A Use Case for Natural Language Processing Methods

Introduction: Recreational and medical cannabis use (CU) information is often available within the electronic health record (EHR) in a format that is ...

Classification of Adolescent Drinking via Behavioral, Biological, and Environmental Features: A Machine Learning Approach with Bias Control

In 2024, approximately 30% of U.S. adolescents reported having consumed alcohol at least once in their lifetime, with about 25% of these individuals e...