Imagen de Portada

Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Geraci, Joseph, Qorri, Bessi, Cumbaa, Christian, Tsay, Mike, Leonczyk, Paul, Pani, Luca
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Quantitative Methods
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

TrialMatchAI: An End-to-End AI-powered Clinical Trial Recommendation System to Streamline Patient-to-Trial Matching
por: Abdallah, Majd, et al.
Publicado: (2025)

Quantifying AI-to-Clinical Translation: The Algorithm-to-Outcome Concordance (AOC) Framework
por: Yu, Xiyao, et al.
Publicado: (2025)

ChemRecon: a Consolidated Meta-Database Platform for Biochemical Data Integration
por: Eriksen, Casper Asbjørn, et al.
Publicado: (2026)

How Light Reshapes the Mind. An Active Inference Framework for the Cognitive and Emotional Effects of Indoor Lighting
por: Possati, Luca M.
Publicado: (2026)

Negative Spillover: A Potential Source of Bias in Pragmatic Clinical Trials
por: Mann, Sean
Publicado: (2023)

Integrative Prognostic Modeling of Breast Cancer Survival with Gene Expression and Clinical Data
por: Amevor, Robert, et al.
Publicado: (2025)

Two for the Price of One: Integrating Large Language Models to Learn Biophysical Interactions
por: Clark, Joseph D., et al.
Publicado: (2025)

Testing machine learning of multimodal digital markers for early detection of cognitive impairment in Alzheimer's Disease rhoda
por: Joseph Geraci, et al.
Publicado: (2025)

Biomarker Integration and Biosensor Technologies Enabling AI-Driven Insights into Biological Aging
por: Kushner, Jared A, et al.
Publicado: (2025)

Shifts in Brain Dynamics and Drivers of Consciousness State Transitions
por: Bodenheimer, Joseph, et al.
Publicado: (2024)

From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research
por: Muneer, Amgad, et al.
Publicado: (2025)

AI-Driven Hybrid Ecological Model for Predicting Oncolytic Viral Therapy Dynamics
por: Uthamacumaran, Abicumaran, et al.
Publicado: (2025)

MM-DADM: Multimodal Drug-Aware Diffusion Model for Virtual Clinical Trials
por: Shao, Qian, et al.
Publicado: (2025)

Reinforcement Learning for Clinical Reasoning: Aligning LLMs with ACR Imaging Appropriateness Criteria
por: Tziakouri, Anni, et al.
Publicado: (2025)

MDAgent: A Multi-Agent Framework for End-to-End Molecular Dynamics Research
por: Ma, Zhenyu, et al.
Publicado: (2026)

Infrared Microscopy of Biochemistry and Metabolism in Single Living Eukaryotic Cells
por: Quaroni, Luca
Publicado: (2025)

Bridging Clinical Narratives and ACR Appropriateness Guidelines: A Multi-Agent RAG System for Medical Imaging Decisions
por: Pambudi, Satrio, et al.
Publicado: (2025)

Literature Mining System for Nutraceutical Biosynthesis: From AI Framework to Biological Insight
por: Sun, Xinyang, et al.
Publicado: (2025)

Evaluating New AI Cell Foundation Models on Challenging Kidney Pathology Cases Unaddressed by Previous Foundation Models
por: Wang, Runchen, et al.
Publicado: (2025)

OMOP ETL Framework for Semi-Structured Health Data
por: Desmond, Jacob, et al.
Publicado: (2025)

An LLM-Powered Clinical Calculator Chatbot Backed by Verifiable Clinical Calculators and their Metadata
por: Kumar, Niranjan, et al.
Publicado: (2025)

Soft Modes as a Predictive Framework for Low Dimensional Biological Systems across Scales
por: Russo, Christopher Joel, et al.
Publicado: (2024)

Beyond P-Values: Importing Quantitative Finance's Risk and Regret Metrics for AI in Learning Health Systems
por: Chakraborty, Richik
Publicado: (2026)

A Semi-Supervised Inf-Net Framework for CT-Based Lung Nodule Analysis with a Conceptual Extension Toward Genomic Integration
por: Mobini, Fateme, et al.
Publicado: (2025)

A Multimodal Foundation Model of Spatial Transcriptomics and Histology for Biological Discovery and Clinical Prediction
por: Xiang, Jinxi, et al.
Publicado: (2026)

Frailty Assessment in Aortic Stenosis based on Dynamic Interconnection between Cardiac and Motor Systems
por: Arrué, Patricio, et al.
Publicado: (2024)

An Active Learning Framework for Data-Efficient, Human-in-the-Loop Enzyme Function Prediction
por: Babjac, Ashley, et al.
Publicado: (2026)

Integrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data
por: Zahoor, Sheresh, et al.
Publicado: (2025)

Modeling PROTAC Degradation Activity with Machine Learning
por: Ribes, Stefano, et al.
Publicado: (2024)

ECKO: Explainable Clinical Knowledge for Oncology
por: Silva, Marta Contreiras, et al.
Publicado: (2025)

Enhancing Clinical Data Warehouses with Provenance and Large File Management: The gitOmmix Approach for Clinical Omics Data
por: Wack, Maxime, et al.
Publicado: (2024)

To Remember, To Adapt, To Preempt: A Stable Continual Test-Time Adaptation Framework for Remote Physiological Measurement in Dynamic Domain Shifts
por: Chu, Shuyang, et al.
Publicado: (2025)

GenoHoption: Bridging Gene Network Graphs and Single-Cell Foundation Models
por: Cheng, Jiabei, et al.
Publicado: (2024)

Disentangling Proxies of Demographic Adjustments in Clinical Equations
por: Shah, Aashna P., et al.
Publicado: (2025)

VIGIL: Vision-Language Guided Multiple Instance Learning Framework for Ulcerative Colitis Histological Healing Prediction
por: Qiu, Zhengxuan, et al.
Publicado: (2025)

Low-fat diets and testosterone in men: Systematic review and meta-analysis of intervention studies
por: Whittaker, Joseph, et al.
Publicado: (2022)

Explainable Deep Learning Framework for SERS Bio-quantification
por: Zaki, Jihan K., et al.
Publicado: (2024)

Antibody Consumption-Driven Dynamic Competition: A Systems Hypothesis for the Transition from Acute Immune Response to Post-Infection Sequelae
por: Qiru, Shi
Publicado: (2025)

Heart Rate Variability Patterns Reflect Yoga Intervention in Chronically Stressed Pregnant Women: A Quasi-Randomized Controlled Trial
por: Mayer, Marlene J E, et al.
Publicado: (2025)

Deciphering Cell Systems: Machine Learning Perspectives And Approaches For The Analysis Of Single-Cell Data
por: Yang, Yongjian
Publicado: (2024)