Latest AI and machine learning research in prescriptions for healthcare professionals.
Next-token prediction is the fundamental principle for training large language models (LLMs), and reinforcement learning (RL) further enhances their reasoning performance. As an effective way to model language, image, video, and other modalities, the use of LLMs for end-to-end extraction of structured visual representations, such as scene graphs, remains underexplored. It requires the model to a...
This study presents an ensemble-based approach for cocoa pod disease classification by integrating transfer learning with three ensemble learning strategies: Bagging, Boosting, and Stacking. Pre-trained convolutional neural networks, including VGG16, VGG19, ResNet50, ResNet101, InceptionV3, and Xception, were fine-tuned and employed as base learners to detect three disease categories: Black Pod ...
Objective: Create precise, structured, data-backed guidelines for type 2 diabetes treatment progression, suitable for clinical adoption. Research ...
Asthma is a chronic respiratory condition that affects millions of people worldwide. While this condition can be managed by administering controller...
Radio Frequency (RF) sensing technologies have experienced significant growth due to the widespread adoption of RF devices and the Internet of Thing...
Medical Visual Language Models have shown great potential in various healthcare applications, including medical image captioning and diagnostic assi...
Images not only depict objects but also encapsulate rich interactions between them. However, generating faithful and high-fidelity images involving ...
Animal-robot interaction (ARI) remains an unexplored challenge in robotics, as robots struggle to interpret the complex, multimodal communication cu...
Visual understanding is inherently contextual -- what we focus on in an image depends on the task at hand. For instance, given an image of a person ...
Learning the response of single-cells to various treatments offers great potential to enable targeted therapies. In this context, neural optimal tra...
Opioid use disorder (OUD) is a leading health problem that affects individual well-being as well as general public health. Due to a variety of reaso...
This study reveals the important role of prevention care and medication adherence in reducing hospitalizations. By using a structured dataset of 1,1...
Physics-Informed Kolmogorov-Arnold Networks (PIKANs) are gaining attention as an effective counterpart to the original multilayer perceptron-based P...
Existing learning models often exhibit poor generalization when deployed across diverse scenarios. It is mainly due to that the underlying reference...
Loco-manipulation -- coordinated locomotion and physical interaction with objects -- remains a major challenge for legged robots due to the need for...
Modern search systems use a multi-stage architecture to deliver personalized results efficiently. Key stages include retrieval, pre-ranking, full ra...
Mild cognitive impairment (MCI) may affect up to 20% of people over 65. Global incidence of MCI is increasing, and technology is being explored for ...
Human pose and shape (HPS) estimation presents challenges in diverse scenarios such as crowded scenes, person-person interactions, and single-view r...
Adverse Drug Events (ADEs), harmful medication effects, pose significant healthcare challenges, impacting patient safety and costs. This study evalu...
Although digital breast tomosynthesis (DBT) improves diagnostic performance over full-field digital mammography (FFDM), false-positive recalls remai...