AIMC Topic: Risk Assessment

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An artificial intelligence application to predict prolonged dependence on mechanical ventilation among patients with critical orthopaedic trauma: an establishment and validation study.

BMC musculoskeletal disorders
BACKGROUND: Prolonged dependence on mechanical ventilation is a common occurrence in clinical ICU patients and presents significant challenges for patient care and resource allocation. Predicting prolonged dependence on mechanical ventilation is cruc...

Development of an individualized dementia risk prediction model using deep learning survival analysis incorporating genetic and environmental factors.

Alzheimer's research & therapy
BACKGROUND: Dementia is a major public health challenge in modern society. Early detection of high-risk dementia patients and timely intervention or treatment are of significant clinical importance. Neural network survival analysis represents the mos...

Assessing the value of deep neural networks for postoperative complication prediction in pancreaticoduodenectomy patients.

PloS one
INTRODUCTION: Pancreaticoduodenectomy (PD) for patients with pancreatic ductal adenocarcinoma (PDAC) is associated with a high risk of postoperative complications (PoCs) and risk prediction of these is therefore critical for optimal treatment plannin...

Attention-based image segmentation and classification model for the preoperative risk stratification of thyroid nodules.

World journal of surgery
BACKGROUND: Despite widespread use of standardized classification systems, risk stratification of thyroid nodules is nuanced and often requires diagnostic surgery. Genomic sequencing is available for this dilemma however, costs and access restricts g...

Improving robustness by action correction via multi-step maximum risk estimation.

Neural networks : the official journal of the International Neural Network Society
Certifying robustness against external uncertainties throughout the control process to reduce the risk of instability is very important. Most existing approaches based on adversarial learning use a fixed parameter to adjust the intensity of adversari...

Using AI to prevent the insect apocalypse: toward new environmental risk assessment procedures.

Current opinion in insect science
Insect populations are declining globally, with multiple potential drivers identified. However, experimental data are needed to understand their relative contributions. We highlight the sublethal effects of pesticides at field-relevant concentrations...

Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study.

Medicina (Kaunas, Lithuania)
: Venous thromboembolism (VTE) can be the first manifestation of an underlying cancer. This study aimed to develop a predictive model to assess the risk of occult cancer between 30 days and 24 months after a venous thrombotic event using machine lear...

Predicting lack of clinical improvement following varicose vein ablation using machine learning.

Journal of vascular surgery. Venous and lymphatic disorders
OBJECTIVE: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LC...