Latest AI and machine learning research in pain management for healthcare professionals.
The task of understanding and interpreting the complex information encoded within genomic sequences remains a grand challenge in biological research and clinical applications. In this context, recent advancements in large language model research have led to the development of both encoder-only and decoder-only foundation models designed to decode intricate information in DNA sequences. However, ...
There are numerous behavioural, social and environmental factors that influence the symptomatology of a chronic health condition. These factors and how they manifest are often very specific to the individual, which creates challenges for applying macro population health approaches and insights to guide treatment. An artificial intelligence system, referred to as a non-axiomatic reasoning system (N...
An innovative chatbot incorporates a drawing tool allowing users to draw pictures that symbolise the nature of their chronic pain. Rather than simply ...
Low back pain (LBP) is a leading cause of disability globally. Following the onset of LBP and subsequent treatment, adequate patient education is cr...
This research dives into exploring the dark mode effects on students of a university. Research is carried out implementing the dark mode in e-Learni...
The exponential growth of neuroscientific data necessitates platforms that facilitate data management and multidisciplinary collaboration. In this p...
This work presents WarmSwap, a novel provider-side cold-start optimization for serverless computing. This optimization reduces cold-start time when ...
Precise and timely forecasting of blood glucose levels is essential for effective diabetes management. While extensive research has been conducted o...
Delineating and classifying individual cells in microscopy tissue images is inherently challenging yet remains essential for advancements in medical...
Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs...
BACKGROUND AND METHODS: In this narrative review, we introduce key artificial intelligence (AI) and machine learning (ML) concepts, aimed at headache ...
PURPOSE: Identifying cancer symptoms in electronic health record (EHR) narratives is feasible with natural language processing (NLP). However, more ef...
Migraine, a prevalent neurological disorder, has been associated with various ocular manifestations suggestive of neuronal and microvascular deficit...
Purpose To assess the performance of a local open-source large language model (LLM) in various information extraction tasks from real-life emergency b...
BACKGROUND: Early medical attention after concussion may minimize symptom duration and burden; however, many concussions are undiagnosed or have a del...
This study compares the effectiveness of the traditional minimum circle detection strategy, i.e. Welzl's algorithm, and the state-of-the-art nnU-Net i...
The limited size of pain datasets are a challenge in developing robust deep learning models for pain recognition. Transfer learning approaches are o...
Glaucoma is a chronic eye disease characterized by optic neuropathy, leading to irreversible vision loss. It progresses gradually, often remaining u...