To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion rad...
Ixodes scapularis ticks are the primary vector of Lyme disease (LD) in North America, and their range has expanded into southeastern and southcentral Canada with climate change. This study presents a comprehensive machine learning (ML) framework to e...
BACKGROUND: Chatbots have demonstrated promising capabilities in medicine, scoring passing grades for board examinations across various specialties. However, their tendency to express high levels of confidence in their responses, even when incorrect,...
BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidity and mortality rates. Traditional early warning models rely on binary (0/1) classification methods, which issue alerts only when predefined threshol...
Examining the cancer risk associated with oral groundwater (GW) intake is crucial, particularly in regions heavily reliant on GW for human consumption and agriculture. The study was based on real field investigations and controlled laboratory experim...
Neural networks : the official journal of the International Neural Network Society
Apr 25, 2025
For the multi-class classification problems, we propose a new probabilistic output classifier called kernel-free quadratic surface support vector machine for conditional probability estimation (CPSQSVM), which is based on a newly developed binary cla...
Neural networks : the official journal of the International Neural Network Society
Apr 24, 2025
Long-term power load forecasting is critical for power system planning but is constrained by intricate temporal patterns. Transformer-based models emphasize modeling long- and short-term dependencies yet encounter limitations from complexity and para...
For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be processed from point inventories to surface predictive maps. For large-scale predictive mapping, very fe...
Neural networks : the official journal of the International Neural Network Society
Jan 27, 2025
One-class learning has many application potentials in novelty, anomaly, and outlier detection systems. It aims to distinguish both positive and negative samples with a model trained via only positive samples or one-class annotated samples. With the d...
Neural networks : the official journal of the International Neural Network Society
Jan 27, 2025
Effective uncertainty estimation is becoming increasingly attractive for enhancing the reliability of neural networks. This work presents a novel approach, termed Credal-Set Interval Neural Networks (CreINNs), for classification. CreINNs retain the f...
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