AIMC Topic: Humans

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Dual-tower model with semantic perception and timespan-coupled hypergraph for next-basket recommendation.

Neural networks : the official journal of the International Neural Network Society
Next basket recommendation (NBR) is an essential task within the realm of recommendation systems and is dedicated to the anticipation of user preferences in the next moment based on the analysis of users' historical sequences of engaged baskets. Curr...

A resonant quadruped piezoelectric robot inspired by human butterfly swimming patterns.

Ultrasonics
Piezoelectric micro-robots have gained considerable attention in rescue and medical applications due to their rapid response times and high positioning accuracy. In this paper, inspired by the human butterfly locomotion pattern, we propose a novel re...

Explainable exercise recommendation with knowledge graph.

Neural networks : the official journal of the International Neural Network Society
Recommending suitable exercises and providing the reasons for these recommendations is a highly valuable task, as it can significantly improve students' learning efficiency. Nevertheless, the extensive range of exercise resources and the diverse lear...

M4Net: Multi-level multi-patch multi-receptive multi-dimensional attention network for infrared small target detection.

Neural networks : the official journal of the International Neural Network Society
The detection of infrared small targets is getting more and more attention, and has a wider application in both military and civilian fields. The traditional infrared small target detection methods heavily rely on the setting of manual features, and ...

Early prediction of intensive care unit admission in emergency department patients using machine learning.

Australian critical care : official journal of the Confederation of Australian Critical Care Nurses
BACKGROUND: The timely identification and transfer of critically ill patients from the emergency department (ED) to the intensive care unit (ICU) is important for patient care and ED workflow practices.

Automatic segmentation of pericardial adipose tissue from cardiac MR images via semi-supervised method with difference-guided consistency.

Medical physics
BACKGROUND: Accurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high co...

Semi-supervised medical image segmentation network based on mutual learning.

Medical physics
BACKGROUND: Semi-supervised learning provides an effective means to address the challenge of insufficient labeled data in medical image segmentation tasks. However, when a semi-supervised segmentation model is overfitted and exhibits cognitive bias, ...

Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences.

Medical physics
BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations from unlabeled data, and enable fine-tuning on downstream tasks with limited labeled examples. Self-pretraining is a SSL approach that uses curated do...

Machine learning for predicting poor outcomes in aneurysmal subarachnoid hemorrhage: A systematic review and meta-analysis involving 8445 participants.

Clinical neurology and neurosurgery
Early prediction of poor outcomes in patients impacted with aneurysmal subarachnoid hemorrhage (aSAH) is crucial for timely intervention and effective management. This systematic review and meta-analysis aimed to evaluate the performance of machine l...

A prognostic and predictive model based on deep learning to identify optimal candidates for intensity-modulated radiotherapy alone in patients with stage II nasopharyngeal carcinoma: A retrospective multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To develop and validate a prognostic and predictive model integrating deep learning MRI features and clinical information in patients with stage II nasopharyngeal carcinoma (NPC) to identify patients with a low risk of progression for whom i...