AIMC Topic: Uncertainty

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Reliability of uncertainty quantification methods for deep learning auto-segmentation in head and neck organs at risk.

Physics in medicine and biology Oct 17, 2025
Deep learning auto-segmentation has greatly advanced contouring in radiotherapy. However, quality assurance remains necessary due to performance fluctuation among individual patients. This manual process reintroduces variability and partially reduces...
Deep Learning Image Processing, Computer-Assisted Head and Neck Neoplasms Humans Reproducibility of Results Uncertainty Organs at Risk Automation
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Upgrading Reliability in Molecular Property Prediction by Robust Quantification of Uncertainty from Machine Learning Models.

Journal of chemical information and modeling Oct 8, 2025
Reliable methods to quantify the predictive uncertainty of machine learning (ML) models can significantly increase the impact of molecular property prediction and are routinely used in applications like active learning and ML-guided property optimiza...
Machine Learning Structure-Activity Relationship Reproducibility of Results Uncertainty
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Early warning of regime switching in a financial time series: A heteroskedastic network model.

PloS one Oct 8, 2025
Regime switching in a time series is an important and challenging issue in complex financial system analysis. Existing regime models have focused on the features of fluctuations at a single point in financial time series, often neglecting time series...
Nonlinear Dynamics Investments Machine Learning Uncertainty Markov Chains Humans Time Factors Algorithms Models, Economic Financial Management
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Multi-step ahead streamflow and uncertainty forecasting using a HyMoLAP rainfall-runoff model-based framework integrated with Bayesian neural networks in the Ouémé river basin, Benin.

PloS one Oct 7, 2025
Multi-step forecasting is crucial for capturing future streamflow variations and managing water resources but remains challenging due to limited accuracy of upstream flow forecasts and meteorological predictions over lead times. While data-driven met...
Rain Water Movements Benin Uncertainty Forecasting Models, Theoretical Bayes Theorem Rivers Neural Networks, Computer
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A phase-aware Cross-Scale U-MAMba with uncertainty-aware segmentation and Switch Atrous Bifovea EfficientNetB7 classification of kidney lesion subtype.

Lasers in medical science Sep 30, 2025
Kidney lesion subtype identification is essential for precise diagnosis and personalized treatment planning. However, achieving reliable classification remains challenging due to factors such as inter-patient anatomical variability, incomplete multi-...
Uncertainty Image Processing, Computer-Assisted Kidney Neoplasms Tomography, X-Ray Computed Humans Deep Learning
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MOLECULE: Molecular-dynamics and Optimized deep Learning for Entropy-regularized Classification and Uncertainty-aware Ligand Evaluation.

Journal of chemical theory and computation Sep 11, 2025
Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' pred...
Ligands Protein Kinase Inhibitors Entropy Uncertainty Deep Learning Molecular Dynamics Simulation Drug Discovery
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Utilizing CNNs for classification and uncertainty quantification for 15 families of European fly pollinators.

PloS one Sep 10, 2025
Pollination is essential for maintaining biodiversity and ensuring food security, and in Europe it is primarily mediated by four insect orders (Coleoptera, Diptera, Hymenoptera, Lepidoptera). However, traditional monitoring methods are costly and tim...
Pollination Uncertainty Europe Neural Networks, Computer Diptera Animals
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Minimizing and quantifying uncertainty in AI-informed decisions: Applications in medicine.

Proceedings of the National Academy of Sciences of the United States of America Aug 20, 2025
AI is now a cornerstone of modern dataset analysis. In many real world applications, practitioners are concerned with controlling specific kinds of errors, rather than minimizing the overall number of errors. For example, biomedical screening assays ...
Humans Uncertainty Neoplasms Artificial Intelligence Liquid Biopsy Algorithms
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Uncertainty-Aware Deep Learning and Structural Feature Analysis for Reliable Nephrotoxicity Prediction.

Journal of chemical information and modeling Aug 19, 2025
Nephrotoxicity remains a critical safety concern in drug development and clinical practice. Despite their significance, existing computational models for nephrotoxicity prediction face challenges related to limited precision and reliability. To addre...
Uncertainty Humans Neural Networks, Computer Kidney Deep Learning Drug-Related Side Effects and Adverse Reactions
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Uncertainty-Informed Screening for Safer Solvents Used in the Synthesis of Perovskites via Language Models.

Journal of chemical information and modeling Jul 22, 2025
Automated data curation for niche scientific topics, where data quality and contextual accuracy are paramount, poses significant challenges. Bidirectional contextual models such as BERT and ELMo excel in contextual understanding and determinism. Howe...
Uncertainty Oxides Solvents Titanium Calcium Compounds
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