Latest AI and machine learning research in risk management for healthcare professionals.
Hereditary thoracic aortic diseases (HTAD) are often associated with multifaceted phenotypic manifestations in different anatomical districts, including skeletal abnormalities. Therefore, diagnostic criteria account for multiple parameters to compute a systemic risk score. Despite the forefoot is known to be different in HTAD, its complex morphology is difficult to be quantified objectively and it...
Stroke is one of the leading causes of mortality and long-term disability in adults over 18 years of age globally and its increasing incidence has become a global public health concern. Accurate stroke prediction is highly valuable for early intervention and treatment. Previous studies have utilized statistical and machine learning techniques to develop stroke prediction models. Only a few have in...
The detailed assessment of fetal brain maturation and development involves morphological evaluation, gyration analysis, and reliable biometric measure...
Major depressive disorder (MDD) remains challenging to treat, with many patients failing to respond adequately to existing therapies. Patients with MD...
Considering numerous radiological images and the heavy workload of writing corresponding reports in clinical work, it is significant to leverage artif...
Despite CBT’s status as a first-line treatment, a substantial proportion of patients does not experience sufficient symptom relief. Recent advances in...
The integration of artificial intelligence (AI) has revolutionized medical research, offering innovative solutions for data collection, patient engage...
Common diseases exhibit substantial heritability, and GWAS of these diseases have revealed hundreds of thousands of high-frequency disease susceptibil...
Incomplete reporting of a study’s methods and results hinders efforts to evaluate and reproduce research findings in randomized controlled trials (RCT...
Randomized controlled trials (RCTs) provide the highest level of clinical evidence but are often limited by cost, time, and ethical constraints. Emula...
Anemia, or low blood hemoglobin (Hb), affects one third of the world population, and is particularly prevalent in women and children in lower resource...
To evaluate the potential of LLMs to generate sequence-level brain MRI protocols. A dataset of 150 brain MRI cases was derived from imaging request fo...
In this study, we develop and validate an interpretable machine learning (ML) model that integrates a hybrid Swarm Intelligence (SI)–based feature sel...
To explore how advocacy has been defined, conceptualised and implemented within nursing, midwifery and the allied health professions. A secondary aim ...
Polygenic risk scores (PRSs) serve as quantitative metrics of genetic liability for various conditions. Traditionally calculated as an effect size wei...
Fluoroquinolones, while clinically indispensable, carry underappreciated cardiovascular risks, particularly QT prolongation and life-threatening arrhy...
Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection, and impaired qualit...
Allostatic load refers to the cumulative burden of stress and life events that involve the interaction of various physiological systems at differing l...
The management of cancer care generates vast amounts of data, collected in the clinical registry; however, the interpretation of these unstandardized ...
Programming deep brain stimulation (DBS) of the subthalamic nucleus for optimal symptom control in Parkinson’s Disease (PD) requires time and trained ...