Artificial Intelligence for Biomedical Data
portes grátis
Artificial Intelligence for Biomedical Data
First International Workshop, AIBio 2025, Held in Conjunction with the European Conference on Artificial Intelligence, ECAI 2025, Bologna, Italy, October 25-26, 2025, Proceedings
Tommasino, Cristian; Bernardini, Michele; Russo, Cristiano
Springer Nature Switzerland AG
02/2026
266
Mole
Inglês
9783032172150
15 a 20 dias
Descrição não disponível.
.- AI for Desease.
.- Improving Early Sepsis Onset Prediction Through Federated Learning.
.- Experimenting Federated AI Models for Hematological Diseases.
.- Hearing Impairment Assessment in Infants through Explainable Computer Vision Analysis of Facial Features.
.- Type 2 Diabetes Prediction from multi-center Electronic Health Records in General Practice using Machine Learning.
.- Self-Attention as a Predictor of EEG Anomalies.
.- Cross-dataset Multivariate Time-series Model for Parkinson's Diagnosis via Keyboard Dynamics.
.- Assessment and Compliance of Personalized Machine Learning Pharmacokinetic Models in the European Regulatory Environment.
.- Data Generation and Augmentation.
.- Knowledge Graph-Enhanced Retrieval-Augmented Generation for Nutrigenetics.
.- Generative Data Augmentation by Dataset Distillation.
.- Semantic Similarity in Radiology Reports via LLMs and NER.
.- From Scarce to Sufficient: Imaginary Image-like Features via Diffusion Models for Imbalanced Medical Data.
.- Flow-Based Synthetic Data Generation: A Unified Approach for Biomedical Tasks.
.- Multimodal Techniques.
.- Multimodal Machine Learning Architecture for Predictive Diagnosis and Treatment of Ophthalmic Diseases.
.- GNN-based Multimodal Analysis of Brain Anatomical and Functional Features for Parkinson's Disease and Cognitive Decline Detection.
.- Data Donation for Digital Twins in Healthcare: Potential and Challenges in the European Context.
.- Image Segmentation.
.- Quality-Guided Focal Loss: Enhancing Minority Class Detection in Haematological Imaging.
.- Auto-prompting Foundation Models for Clinical Segmentation: The Case of Pathological Scapula.
.- Keynote Papers.
.- Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis.
.- Transcending the Annotation Bottleneck: AI-Powered Discovery in Biology and Medicine.
.- Increasing Data Availability Through Standardization: Unlocking AI in Digital Pathology.
.- Why accuracy isn't enough. Rethinking Model Evaluation in Clinical AI with a user-centered utility metric.
.- Improving Early Sepsis Onset Prediction Through Federated Learning.
.- Experimenting Federated AI Models for Hematological Diseases.
.- Hearing Impairment Assessment in Infants through Explainable Computer Vision Analysis of Facial Features.
.- Type 2 Diabetes Prediction from multi-center Electronic Health Records in General Practice using Machine Learning.
.- Self-Attention as a Predictor of EEG Anomalies.
.- Cross-dataset Multivariate Time-series Model for Parkinson's Diagnosis via Keyboard Dynamics.
.- Assessment and Compliance of Personalized Machine Learning Pharmacokinetic Models in the European Regulatory Environment.
.- Data Generation and Augmentation.
.- Knowledge Graph-Enhanced Retrieval-Augmented Generation for Nutrigenetics.
.- Generative Data Augmentation by Dataset Distillation.
.- Semantic Similarity in Radiology Reports via LLMs and NER.
.- From Scarce to Sufficient: Imaginary Image-like Features via Diffusion Models for Imbalanced Medical Data.
.- Flow-Based Synthetic Data Generation: A Unified Approach for Biomedical Tasks.
.- Multimodal Techniques.
.- Multimodal Machine Learning Architecture for Predictive Diagnosis and Treatment of Ophthalmic Diseases.
.- GNN-based Multimodal Analysis of Brain Anatomical and Functional Features for Parkinson's Disease and Cognitive Decline Detection.
.- Data Donation for Digital Twins in Healthcare: Potential and Challenges in the European Context.
.- Image Segmentation.
.- Quality-Guided Focal Loss: Enhancing Minority Class Detection in Haematological Imaging.
.- Auto-prompting Foundation Models for Clinical Segmentation: The Case of Pathological Scapula.
.- Keynote Papers.
.- Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis.
.- Transcending the Annotation Bottleneck: AI-Powered Discovery in Biology and Medicine.
.- Increasing Data Availability Through Standardization: Unlocking AI in Digital Pathology.
.- Why accuracy isn't enough. Rethinking Model Evaluation in Clinical AI with a user-centered utility metric.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Artificial Intelligence in Biomedical Research;Digital Pathology;Whole-Slide Imaging;Multi-omics Data Integration;Deep Learning for Medical Imaging;Edge Computing in Biomedical AI;Cloud Computing for Health Data;5G/6G for Digital Health;Explainable AI;Interpretability in Clinical AI;Fair Machine Learning;Biomarker Discovery;Precision Medicine;Multi-modal Biomedical Data;Telemedicine;Remote Patient Monitoring;Computational Biology;Computer Tomography;Medical Imaging Analysis;Synthetic Data Generation
.- AI for Desease.
.- Improving Early Sepsis Onset Prediction Through Federated Learning.
.- Experimenting Federated AI Models for Hematological Diseases.
.- Hearing Impairment Assessment in Infants through Explainable Computer Vision Analysis of Facial Features.
.- Type 2 Diabetes Prediction from multi-center Electronic Health Records in General Practice using Machine Learning.
.- Self-Attention as a Predictor of EEG Anomalies.
.- Cross-dataset Multivariate Time-series Model for Parkinson's Diagnosis via Keyboard Dynamics.
.- Assessment and Compliance of Personalized Machine Learning Pharmacokinetic Models in the European Regulatory Environment.
.- Data Generation and Augmentation.
.- Knowledge Graph-Enhanced Retrieval-Augmented Generation for Nutrigenetics.
.- Generative Data Augmentation by Dataset Distillation.
.- Semantic Similarity in Radiology Reports via LLMs and NER.
.- From Scarce to Sufficient: Imaginary Image-like Features via Diffusion Models for Imbalanced Medical Data.
.- Flow-Based Synthetic Data Generation: A Unified Approach for Biomedical Tasks.
.- Multimodal Techniques.
.- Multimodal Machine Learning Architecture for Predictive Diagnosis and Treatment of Ophthalmic Diseases.
.- GNN-based Multimodal Analysis of Brain Anatomical and Functional Features for Parkinson's Disease and Cognitive Decline Detection.
.- Data Donation for Digital Twins in Healthcare: Potential and Challenges in the European Context.
.- Image Segmentation.
.- Quality-Guided Focal Loss: Enhancing Minority Class Detection in Haematological Imaging.
.- Auto-prompting Foundation Models for Clinical Segmentation: The Case of Pathological Scapula.
.- Keynote Papers.
.- Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis.
.- Transcending the Annotation Bottleneck: AI-Powered Discovery in Biology and Medicine.
.- Increasing Data Availability Through Standardization: Unlocking AI in Digital Pathology.
.- Why accuracy isn't enough. Rethinking Model Evaluation in Clinical AI with a user-centered utility metric.
.- Improving Early Sepsis Onset Prediction Through Federated Learning.
.- Experimenting Federated AI Models for Hematological Diseases.
.- Hearing Impairment Assessment in Infants through Explainable Computer Vision Analysis of Facial Features.
.- Type 2 Diabetes Prediction from multi-center Electronic Health Records in General Practice using Machine Learning.
.- Self-Attention as a Predictor of EEG Anomalies.
.- Cross-dataset Multivariate Time-series Model for Parkinson's Diagnosis via Keyboard Dynamics.
.- Assessment and Compliance of Personalized Machine Learning Pharmacokinetic Models in the European Regulatory Environment.
.- Data Generation and Augmentation.
.- Knowledge Graph-Enhanced Retrieval-Augmented Generation for Nutrigenetics.
.- Generative Data Augmentation by Dataset Distillation.
.- Semantic Similarity in Radiology Reports via LLMs and NER.
.- From Scarce to Sufficient: Imaginary Image-like Features via Diffusion Models for Imbalanced Medical Data.
.- Flow-Based Synthetic Data Generation: A Unified Approach for Biomedical Tasks.
.- Multimodal Techniques.
.- Multimodal Machine Learning Architecture for Predictive Diagnosis and Treatment of Ophthalmic Diseases.
.- GNN-based Multimodal Analysis of Brain Anatomical and Functional Features for Parkinson's Disease and Cognitive Decline Detection.
.- Data Donation for Digital Twins in Healthcare: Potential and Challenges in the European Context.
.- Image Segmentation.
.- Quality-Guided Focal Loss: Enhancing Minority Class Detection in Haematological Imaging.
.- Auto-prompting Foundation Models for Clinical Segmentation: The Case of Pathological Scapula.
.- Keynote Papers.
.- Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis.
.- Transcending the Annotation Bottleneck: AI-Powered Discovery in Biology and Medicine.
.- Increasing Data Availability Through Standardization: Unlocking AI in Digital Pathology.
.- Why accuracy isn't enough. Rethinking Model Evaluation in Clinical AI with a user-centered utility metric.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Artificial Intelligence in Biomedical Research;Digital Pathology;Whole-Slide Imaging;Multi-omics Data Integration;Deep Learning for Medical Imaging;Edge Computing in Biomedical AI;Cloud Computing for Health Data;5G/6G for Digital Health;Explainable AI;Interpretability in Clinical AI;Fair Machine Learning;Biomarker Discovery;Precision Medicine;Multi-modal Biomedical Data;Telemedicine;Remote Patient Monitoring;Computational Biology;Computer Tomography;Medical Imaging Analysis;Synthetic Data Generation
