Latest AI and machine learning research in primary care for healthcare professionals.
Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed based on single-modal biochemical tests, and imaging data have been used to predict stroke recurrence. However, the prediction accuracy of these models is not sufficiently high. Therefore, this study aimed to collect biochemical detection and magnetic resonance imaging (MRI) data to establish a datase...
Virtual Screening is an essential technique in the early phases of drug discovery, aimed at identifying promising drug candidates from vast molecular libraries. Recently, ligand-based virtual screening has garnered significant attention due to its efficacy in conducting extensive database screenings without relying on specific protein-binding site information. Obtaining binding affinity data for...
The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for p...
This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis,...
Type 2 Diabetes (T2D) is a prevalent lifelong health condition. It is predicted that over 500 million adults will be diagnosed with T2D by 2040. T2D c...
We provide a realist review of product launches for Large Language Models (LLMs) in the healthcare industry. Through a systematic search in the Factiv...
This study leverages data from a Canadian database of primary care Electronic Medical Records to develop machine learning models predicting type 2 dia...
This study introduces a Generative Artificial Intelligence (GenAI) assistant designed to address key challenges in Remote Patient Monitoring (RPM) for...
Diabetes mellitus (DM) is a significant public health issue in Germany, affecting 8 million individuals, with projections suggesting a substantial inc...
Recent advances in SSL enabled novel medical AI models, known as foundation models, offer great potential for better characterizing health from dive...
Electroencephalography (EEG) provides reliable indications of human cognition and mental states. Accurate emotion recognition from EEG remains chall...
Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devic...
Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for...
Background Artificial intelligence (AI) systems can be used to identify interval breast cancers, although the localizations are not always accurate. P...
Traditional Chinese medicine(TCM) placebos are simulated preparations for specific objects and the color simulation in the development of TCM placebos...
The AIDS epidemic has killed 40 million people and caused serious global problems. The identification of new HIV-inhibiting molecules is of great im...
Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors a...
CONTEXT: The presence of metabolic dysfunction-associated steatotic liver disease (MASLD) in patients with diabetes mellitus (DM) is associated with a...
Artificial intelligence (AI) has demonstrated revolutionary potential and wide-ranging applications in the comprehensive management of fundus diseases...
Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice and research. The exponential rise in technology po...