Latest AI and machine learning research in addictions for healthcare professionals.
It has been a longstanding goal within image captioning to move beyond a dependence on object detection. We investigate using superpixels coupled with Vision Language Models (VLMs) to bridge the gap between detector-based captioning architectures and those that solely pretrain on large datasets. Our novel superpixel approach ensures that the model receives object-like features whilst the use of ...
The deformable registration of images of different modalities, essential in many medical imaging applications, remains challenging. The main challenge is developing a robust measure for image overlap despite the compared images capturing different aspects of the underlying tissue. Here, we explore similarity metrics based on functional dependence between intensity values of registered images. Al...
Failure to manage emotional withdrawal symptoms can exacerbate relapse to methamphetamine use. Understanding the neuro-mechanisms underlying methamphe...
The issue of failed weaning is a critical concern in the intensive care unit (ICU) setting. This scenario occurs when a patient experiences difficul...
Image personalization has garnered attention for its ability to customize Text-to-Image generation using only a few reference images. However, a key...
Pain is a complex, multidimensional experience involving significant challenges in both diagnosis and management. While acute pain serves as a critica...
Addictive behaviour is shaped by the dynamic interaction of implicit, bottom-up and explicit, top-down cognitive processes. In alcohol use disorder (A...
In this note, we examine the aggregation of preferences achieved by the Group Policy Optimisation (GRPO) algorithm, a reinforcement learning method ...
Despite extensive research efforts focused on OOD detection on images, OOD detection on nodes in graph learning remains underexplored. The dependenc...
Time series domain adaptation aims to transfer the complex temporal dependence from the labeled source domain to the unlabeled target domain. Recent...
Transformers have become the backbone of neural network architecture for most machine learning applications. Their widespread use has resulted in mu...
Many machine learning techniques rely on minimizing the covariance between output feature dimensions to extract minimally redundant representations ...
Antimicrobial photodynamic therapy (APDT) is a promising antibiotic-free strategy for broad-spectrum infection control in chronic wounds, minimising...
Feature selection is an important but challenging task in causal inference for obtaining unbiased estimates of causal quantities. Properly selected ...
The dose-response relationship between metformin and change in hemoglobin A1c (HbA1c) shows a maximum at 1500-2000 mg/day in patients with type 2 diab...
Importance: Emergency department (ED) returns for mental health conditions pose a major healthcare burden, with 24-27% of patients returning within ...
While tobacco advertising innovates at unprecedented speed, traditional surveillance methods remain frozen in time, especially in the context of soc...
Data assimilation plays a pivotal role in understanding and predicting turbulent systems within geoscience and weather forecasting, where data assim...
OBJECTIVE: To conduct a systematic review on Artificial Intelligence-Mediated Communication (AIMC) behavioral interventions in cancer prevention/contr...
We aim to assist image-based myopia screening by resolving two longstanding problems, "how to integrate the information of ocular images of a pair o...