AIMC Topic: Risk Assessment

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A Machine Learning Algorithm to Identify Patients with Tibial Shaft Fractures at Risk for Infection After Operative Treatment.

The Journal of bone and joint surgery. American volume
BACKGROUND: Risk stratification of individual patients who are prone to infection would allow surgeons to monitor high-risk patients more closely and intervene early when needed. This could reduce infection-related consequences such as increased heal...

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Schizophrenia bulletin
BACKGROUND: Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis.

Machine learning-integrated omics for the risk and safety assessment of nanomaterials.

Biomaterials science
With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessities to advanced electronics, health care products and medicines. Therefore, nanoproducts, however, can...

Letters.

The journal of the American Academy of Psychiatry and the Law

Predicting 2-Day Mortality of Thrombocytopenic Patients Based on Clinical Laboratory Data Using Machine Learning.

Medical care
BACKGROUND: Clinical laboratories have traditionally used a single critical value for thrombocytopenic events. This system, however, could lead to inaccuracies and inefficiencies, causing alarm fatigue and compromised patient safety.

Advancing care for acute gastrointestinal bleeding using artificial intelligence.

Journal of gastroenterology and hepatology
The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision making. Machine learning algorithms have shown promise in outperforming existing clinical risk score...

Applications of artificial intelligence in pancreatic and biliary diseases.

Journal of gastroenterology and hepatology
The application of artificial intelligence (AI) in medicine has increased rapidly with respect to tasks including disease detection/diagnosis, risk stratification, and prognosis prediction. With recent advances in computing power and algorithms, AI h...

Challenges of developing artificial intelligence-assisted tools for clinical medicine.

Journal of gastroenterology and hepatology
Machine learning, a subset of artificial intelligence (AI), is a set of computational tools that can be used to enhance provision of clinical care in all areas of medicine. Gastroenterology and hepatology utilize multiple sources of information, incl...

Early prediction of mortality risk among patients with severe COVID-19, using machine learning.

International journal of epidemiology
BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection ...

Prediction and comparison of postural discomfort based on MLP and quadratic regression.

Journal of occupational health
OBJECTIVE: The objective of this study was to predict postural discomfort based on the deep learning-based regression (multilayer perceptron [MLP] model).