AIMC Topic: Risk Assessment

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Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.

BMC medical informatics and decision making
BACKGROUND: Stroke is one of the leading causes of death and disability worldwide, with a significantly elevated incidence among individuals with hypertension. Conventional risk assessment methods primarily rely on a limited set of clinical parameter...

Using a large language model (ChatGPT) to assess risk of bias in randomized controlled trials of medical interventions: protocol for a pilot study of interrater agreement with human reviewers.

BMC medical research methodology
BACKGROUND: Risk of bias (RoB) assessment is an essential part of systematic reviews that requires reading and understanding each eligible trial and RoB tools. RoB assessment is subject to human error and is time-consuming. Machine learning-based too...

A retrospective cohort study using machine learning to predict coronary artery lesions in children with Kawasaki disease.

BMC pediatrics
BACKGROUND: Kawasaki disease (KD) mainly occurs in children under 5 years old, and the most common complication of KD is coronary artery lesion (CAL). In recent years, the incidence rate of KD has increased year by year worldwide, so it is particular...

Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China.

Scientific reports
As a typical pest affecting corn yield and safety, corn borer causes serious economic losses worldwide. Climate warming has intensified the occurrence of pest outbreaks in recent years, but the associated risk has not been precisely assessed or under...

Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation.

Nature communications
Atrial fibrillation (AF) increases the risk of adverse cardiovascular events, yet the underlying biological mechanisms remain unclear. We evaluate a panel of 12 circulating biomarkers representing diverse pathophysiological pathways in 3817 AF patien...

Predicting adolescent suicide risk using integrated data from adolescents, parents and siblings: An analysis of multiple machine learning models.

Journal of affective disorders
Adolescent suicide is a critical public health issue, yet accurately predicting suicide risk remains challenging. Few studies integrate adolescents' self-reports with mental health, especially suicidality assessments from parents and siblings. This s...

Integrating machine learning for enhanced spatial prediction and risk assessment of soil heavy metal(loid)s.

Environmental pollution (Barking, Essex : 1987)
Accurately predicting the concentrations and spatial distribution of soil heavy metal(loid)s is crucial for effective environmental management and human health risk assessment. However, existing studies are often limited by poor model accuracy, featu...

Evaluation and analysis of risk factors for fractured vertebral recompression post-percutaneous kyphoplasty: a retrospective cohort study based on logistic regression analysis.

BMC musculoskeletal disorders
BACKGROUND: Vertebral recompression after percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures (OVCFs) may lead to recurrent pain, deformity, and neurological impairment, compromising prognosis and quality of life.

COVID-19 risk stratification among older adults: a machine learning approach to identify personal and health-related risk factors.

BMC public health
BACKGROUND: The COVID-19 pandemic highlighted the need to understand factors influencing individuals' risk perceptions and health behaviors. This study aimed to explore the roles of individuals' knowledge, perception, and health-related issues in det...

Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive geriatric assessment.

BMC medical informatics and decision making
BACKGROUND: Lumbar spinal stenosis is one of the most common surgery-requiring conditions of the spine in the aged population. As elderly patients often present with multiple comorbidities and limited physiological reserve, individualized risk assess...