AIMC Topic: Humans

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Radiologists and trainees' perspectives on artificial intelligence.

Radiologia
BACKGROUND AND OBJECTIVES: The purpose of this study was to investigate perspectives held by radiologists on the use of artificial intelligence (AI) in their day-to-day work and to identify factors limiting its routine implementation.

Machine Learning-Based Predictive Models for Patients with Venous Thromboembolism: A Systematic Review.

Thrombosis and haemostasis
BACKGROUND:  Venous thromboembolism (VTE) is a chronic disorder with a significant health and economic burden. Several VTE-specific clinical prediction models (CPMs) have been used to assist physicians in decision-making but have several limitations....

Leveraging Artificial Intelligence to Optimize the Care of Peripheral Artery Disease Patients.

Annals of vascular surgery
Peripheral artery disease is a major atherosclerotic disease that is associated with poor outcomes such as limb loss, cardiovascular morbidity, and death. Artificial intelligence (AI) has seen increasing integration in medicine, and its various appli...

Machine learning based analysis and detection of trend outliers for electromyographic neuromuscular monitoring.

Journal of clinical monitoring and computing
PURPOSE: Neuromuscular monitoring is frequently plagued by artefacts, which along with the frequent unawareness of the principles of this subtype of monitoring by many clinicians, tends to lead to a cynical attitute by clinicians towards these monito...

AI in cellular engineering and reprogramming.

Biophysical journal
During the last decade, artificial intelligence (AI) has increasingly been applied in biophysics and related fields, including cellular engineering and reprogramming, offering novel approaches to understand, manipulate, and control cellular function....

Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion correction technique for high-resolution Cartesian first-pass myocardial perfusion imaging at 3T with whole-heart coverage for both single-slice (SS) a...

Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning.

International journal of computer assisted radiology and surgery
PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol...

Are deep learning classification results obtained on CT scans fair and interpretable?

Physical and engineering sciences in medicine
Following the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications to various automatic diagnosis cases. Unfortunately, most of the deep...

Identification of the best machine learning model for the prediction of driver injury severity.

International journal of injury control and safety promotion
Predicting the injury severities sustained by drivers engaged in road traffic accidents is a key topic of research in road traffic safety. The current study analyzed the driver injury severity (DIS) using twelve machine learning (ML) algorithms. Thes...

Algor-ethics: charting the ethical path for AI in critical care.

Journal of clinical monitoring and computing
The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particula...