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A risk prediction model for venous thromboembolism in hospitalized patients with thoracic trauma: a machine learning, national multicenter retrospective study.

World journal of emergency surgery : WJES
BACKGROUND: Early treatment and prevention are the keys to reducing the mortality of VTE in patients with thoracic trauma. This study aimed to develop and validate an automatic prediction model based on machine learning for VTE risk screening in pati...

Machine learning models for prognosis prediction in regenerative endodontic procedures.

BMC oral health
BACKGROUND: This study aimed to establish and validate machine learning (ML) models to predict the prognosis of regenerative endodontic procedures (REPs) clinically, assisting clinicians in decision-making and avoiding treatment failure.

Factors contributing to chronic ankle instability in parcel delivery workers based on machine learning techniques.

BMC medical informatics and decision making
BACKGROUND: Ankle injuries in parcel delivery workers (PDWs) are most often caused by trips. Ankle sprains have high recurrence rates and are associated with chronic ankle instability (CAI). This study aimed to develop, determine, and compare the pre...

Predicting low density lipoprotein cholesterol target attainment using machine learning in patients with coronary artery disease receiving moderate-dose statin therapy.

Scientific reports
Low-density lipoprotein cholesterol (LDL-C) is an important factor in the development of cardiovascular disease, making its management a key aspect of cardiovascular health. While high-dose statin therapy is often recommended for LDL-C reduction, car...

An efficient approach on risk factor prediction related to cardiovascular disease around Kumbakonam, Tamil Nadu, India, using unsupervised machine learning techniques.

Scientific reports
Nowadays, human beings suffer from varieties of diseases due to the environmental circumstances and their residing habits. Cardiovascular diseases (CVD) are the leading cause of mortality among all diseases. CVDs are heart-related diseases. In early ...

Prediction of mortality risk in critically ill patients with systemic lupus erythematosus: a machine learning approach using the MIMIC-IV database.

Lupus science & medicine
OBJECTIVE: Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE) remains a great challenge in clinical practice. Our study aims to develop and validate predictive models for the mortality risk.

Machine Learning Approach to Identifying Wrong-Site Surgeries Using Centers for Medicare and Medicaid Services Dataset: Development and Validation Study.

JMIR formative research
BACKGROUND: Wrong-site surgery (WSS) is a critical but preventable medical error, often resulting in severe patient harm and substantial financial costs. While protocols exist to reduce wrong-site surgery, underreporting and inconsistent documentatio...

Large Language Models-Supported Thrombectomy Decision-Making in Acute Ischemic Stroke Based on Radiology Reports: Feasibility Qualitative Study.

Journal of medical Internet research
BACKGROUND: The latest advancement of artificial intelligence (AI) is generative pretrained transformer large language models (LLMs). They have been trained on massive amounts of text, enabling humanlike and semantical responses to text-based inputs ...

Few-shot transfer learning for individualized braking intent detection on neuromorphic hardware.

Journal of neural engineering
This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used...

Artificial intelligence for opportunistic osteoporosis screening with a Hounsfield Unit in chronic obstructive pulmonary disease patients.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
INTRODUCTION: To investigate the accuracy of an artificial intelligence (AI) prototype in determining bone mineral density (BMD) in chronic obstructive pulmonary disease (COPD) patients using chest computed tomography (CT) scans.