AIMC Topic: Adult

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A highly scalable deep learning language model for common risks prediction among psychiatric inpatients.

BMC medicine
BACKGROUND: There is a lack of studies exploring the performance of Transformers-based language models in common risks assessment among psychiatric inpatients. We aim to develop a scalable risk assessment model using multidimensional textualized data...

Medical students' knowledge, attitudes, and practices toward generative artificial intelligence in Egypt 2024: a Cross-Sectional study.

BMC medical education
BACKGROUND: Generative artificial intelligence (generative AI) has revolutionized the healthcare system for medical students and their educational process worldwide. Several studies assessed its efficacy in improving medical studies learning, and oth...

Machine learning based differential diagnosis of SAPHO syndrome and secondary bone tumors using whole body bone scintigraphy.

Scientific reports
SAPHO syndrome is an inflammatory disorder with bone and cutaneous manifestations, for which whole-body bone scintigraphy (WBBS) is frequently used in diagnosis. The WBBS findings of SAPHO syndromes and secondary bone tumors (SBT) have overlapping fe...

Robotic radiation shielding system reduces radiation-induced DNA damage in operators performing electrophysiological procedures.

Scientific reports
Fluoroscopically guided electrophysiology (EP) procedures expose operators to low doses of ionizing radiation, which can induce DNA double-strand breaks (DSBs) and raises increasing concerns regarding potential health risks. A novel robotic radiation...

The role of ChatGPT-4o in differential diagnosis and management of vertigo-related disorders.

Scientific reports
To compare the diagnostic accuracy of an artificial intelligence chatbot and clinical experts in vertigo-related diseases and evaluate the ability of the AI chatbot to address vertigo-related issues. 20 clinical questions about vertigo were input to ...

GraftIQ: Hybrid multi-class neural network integrating clinical insight for multi-outcome prediction in liver transplant recipients.

Nature communications
Liver transplant recipients (LTRs) are at risk of graft injury, leading to cirrhosis and reduced survival. Liver biopsy, the diagnostic gold standard, is invasive and risky. We developed a hybrid multi-class neural network (NN) model, 'GraftIQ,' inte...

Data augmentation using masked principal component representation for deep learning-based SSVEP-BCIs.

Journal of neural engineering
Data augmentation has been demonstrated to improve the classification accuracy of deep learning models in steady-state visual evoked potential-based brain-computer interfaces (BCIs), particularly when dealing with limited electroencephalography (EEG)...

Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.

BMC medical informatics and decision making
BACKGROUND: Acute pancreatitis (AP) represents a critical medical condition where timely and precise prediction of in-hospital mortality is crucial for guiding optimal clinical management. This study focuses on the development of advanced machine lea...

Machine learning decision support model construction for craniotomy approach of pineal region tumors based on MRI images.

BMC medical imaging
BACKGROUND: Pineal region tumors (PRTs) are rare but deep-seated brain tumors, and complete surgical resection is crucial for effective tumor treatment. The choice of surgical approach is often challenging due to the low incidence and deep location. ...

Prediction of coronary heart disease based on klotho levels using machine learning.

Scientific reports
The diagnostic accuracy for coronary heart disease (CHD) needs to be improved. Some studies have indicated that klotho protein levels upon admission comprise an independent risk factor for CHD and have clinical value for predicting CHD. This study ai...