Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II / / edited by Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli
| Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II / / edited by Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli |
| Autore | Finkelstein Joseph |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (387 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MoskovitchRobert
ParimbelliEnea |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Education - Data processing Computer networks Database management Data mining Application software Artificial Intelligence Computers and Education Computer Communication Networks Database Management Data Mining and Knowledge Discovery Computer and Information Systems Applications Intel·ligència artificial en medicina |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN |
9783031665356
9783031665349 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Medical imaging analysis. -- 3T to 7T Whole Brain + Skull MRI Translation with Densely Engineered U-Net Network. -- A Sparse Convolutional Autoencoder for Joint Feature Extraction and Clustering of Metastatic Prostate Cancer Images. -- AI in Neuro-Oncology: Predicting EGFR Amplification in Glioblastoma from Whole Slide Images using Weakly Supervised Deep Learning. -- An Exploration of Diabetic Foot Osteomyelitis X-ray Data for Deep Learning Applications. -- Automated Detection and Characterization of Small Cell Lung Cancer Liver Metastases on CT. -- Content-Based Medical Image Retrieval for Medical Radiology Images. -- Cross-Modality Synthesis of T1c MRI from Non-Contrast Images Using GANs: Implications for Brain Tumor Research. -- Harnessing the Power of Graph Propagation in Lung Nodule Detection. -- Histology Image Artifact Restoration with Lightweight Transformer and Diffusion Model. -- Improved Glioma Grade Prediction with Mean Image Transformation. -- Learning to Predict the Optimal Template in Stain Normalization For Histology Image Analysis. -- MRI Brain Cancer Image Detection Application of an Integrated U-Net and ResNet50 Architecture. -- MRI Scan Synthesis Methods based on Clustering and Pix2Pix. -- Supervised Pectoral Muscle Removal in Mammography Images. -- TinySAM-Med3D: A Lightweight Segment Anything Model for Volumetric Medical Imaging with Mixture of Experts. -- Towards a Formal Description of Artificial Intelligence Models and Datasets in Radiology. -- Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification. -- Ultrasound Image Segmentation via a Multi-Scale Salient Network. -- Data integration and multimodal analysis. -- A 360-Degree View for Large Language Models: Early Detection of Amblyopia in Children using Multi-View Eye Movement Recordings. -- Enhancing Anti-VEGF Response Prediction in Diabetic Macular Edema through OCT Features and Clinical Data Integration based on Deep Learning. -- Expert Insight-Enhanced Follow-up Chest X-Ray Summary Generation. -- Integrating multimodal patient data into attention-based graph networks for disease risk prediction. -- Integrative analysis of amyloid imaging and genetics reveals subtypes of Alzheimer progression in early stage. -- Modular Quantitative Temporal Transformer for Biobank-scale Unified Representations. -- Multimodal Fusion of Echocardiography and Electronic Health Records for the Detection of Cardiac Amyloidosis. -- Multi-View $k$-Nearest Neighbor Graph Contrastive Learning on Multi-Modal Biomedical Data. -- Quasi-Orthogonal ECG-Frank XYZ Transformation with Energy-based models and clinical text. -- Explainable AI. -- Do you trust your model explanations? An analysis of XAI performance under dataset shift. -- Explainable AI for Fair Sepsis Mortality Predictive Model. -- Explanations of Augmentation Methods For Deep Learning ECG Classification. -- Exploring the possibility of arrhythmia interpretation of time domain ECG using XAI: a preliminary study. -- Improving XAI Explanations for Clinical Decision-Making – Physicians’ Perspective on Local Explanations in Healthcare. -- Manually-Curated Versus LLM-Generated Explanations for Complex Patient Cases: An Exploratory Study with Physicians. -- On Identifying Effective Investigations with Feature Finding using Explainable AI: an Ophthalmology Case Study. -- Towards Interactive and Interpretable Image Retrieval-Based Diagnosis: Enhancing Brain Tumor Classification with LLM Explanations and Latent Structure Preservation. -- Towards Trustworthy AI in Cardiology: A Comparative Analysis of Explainable AI Methods for Electrocardiogram Interpretation. |
| Record Nr. | UNINA-9910878044503321 |
Finkelstein Joseph
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part I / / edited by Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli
| Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part I / / edited by Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli |
| Autore | Finkelstein Joseph |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (438 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
MoskovitchRobert
ParimbelliEnea |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Education - Data processing Computer networks Database management Data mining Application software Artificial Intelligence Computers and Education Computer Communication Networks Database Management Data Mining and Knowledge Discovery Computer and Information Systems Applications Intel·ligència artificial en medicina |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-66538-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Predictive modelling and disease risk prediction. -- Applying Gaussian Mixture Model for clustering analysis of emergency room patients based on intubation status. -- Bayesian Neural Network to predict antibiotic resistance. -- Boosting multitask decomposition: directness, sequentiality, subsampling, cross-gradients. -- Diagnostic Modeling to Identify Unrecognized Inpatient Hypercapnia Using Health Record Data. -- Enhancing Hypotension Prediction in Real-time Patient Monitoring Through Deep Learning: A Novel Application of XResNet with Contrastive Learning and Value Attention Mechanisms. -- Evaluating the TMR model for multimorbidity decision support using a community-of-practice based methodology. -- Frequent patterns of childhood overweight from longitudinal data on parental and early-life of infants health. -- Fuzzy neural network model based on uni-nullneuron in extracting knowledge about risk factors of Maternal Health. -- Identifying Factors Associated with COVID-19 All-Cause 90-Day Readmission: Machine Learning Approaches. -- Mining Disease Progression Patterns for Advanced Disease Surveillance. -- Minimizing Survey Questions for PTSD Prediction Following Acute Trauma. -- Patient-Centric Approach for Utilising Machine Learning to Predict Health-Related Quality of Life Changes during Chemotherapy. -- Predicting Blood Glucose Levels with LMU Recurrent Neural Networks: A Novel Computational Model. -- Prediction Modelling and Data Quality Assessment for Nursing Scale in a big hospital: a proposal to save resources and improve data quality. -- Process Mining for capacity planning and reconfiguration of a logistics system to enhance the intra-hospital patient transport. Case Study.. -- Radiotherapy Dose Optimization via Clinical Knowledge Based Reinforcement Learning. -- Reinforcement Learning with Balanced Clinical Reward for Sepsis Treatment. -- Secure and Private Vertical Federated Learning for Predicting Personalized CVA Outcomes. -- Smoking Status Classification: A Comparative Analysis of Machine Learning Techniques with Clinical Real World Data. -- The Impact of Data Augmentation on Time Series Classification Models: An In-Depth Study with Biomedical Data. -- The Impact of Synthetic Data on Fall Detection Application. -- Natural Language Processing. -- A Retrieval-Augmented Generation Strategy To Enhance Medical Chatbot Reliability. -- Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging. -- Clinical Reasoning over Tabular Data and Text with Bayesian Networks. -- Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-ranking. -- Enhancing Abstract Screening Classification in Evidence-Based Medicine: Incorporating domain knowledge into pre-trained models. -- Exploring Pre-trained Language Models for Vocabulary Alignment in the UMLS. -- ICU Bloodstream Infection Prediction: A Transformer-Based Approach for EHR Analysis. -- Modeling multiple adverse pregnancy outcomes: Learning from diverse data sources. -- OptimalMEE: Optimizing Large Language Models for Medical Event Extraction through Fine-tuning and Post-hoc Verification. -- Self-Supervised Segment Contrastive Learning for Medical Document Representation 295. -- Sentence-aligned Simplification of Biomedical Abstracts. -- Sequence-Model-Based Medication Extraction from Clinical Narratives in German. -- Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing. -- Bioinformatics and omics. -- Breast cancer subtype prediction model integrating domain adaptation with semi-supervised learning on DNA methylation profiles. -- CI-VAE for Single-Cell: Leveraging Generative-AI to Enhance Disease Understanding. -- ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering. -- Wearable devices, sensors, and robotics. -- Advancements in Non-Invasive AI-Powered Glucose Monitoring: Leveraging Multispectral Imaging Across Diverse Wavelengths. -- Anticipating Stress: Harnessing Biomarker Signals from a Wrist-worn Device for Early Prediction. -- Improving Reminder Apps for Home Voice Assistants. |
| Record Nr. | UNINA-9910878044603321 |
Finkelstein Joseph
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||