AIMC Topic: Humans

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Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Scientific reports
Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity and inter-individual differences involved in this process have not been thoroughly studied. We used m...

Diagnosing malignant distal bile duct obstruction using artificial intelligence based on clinical biomarkers.

Scientific reports
Diagnosing distal bile duct obstruction remains challenging. This study aimed to examine the diagnostic ability of artificial intelligence (AI) based on clinical biomarkers in diagnosing malignant distal bile duct obstruction. A total of 206 patients...

Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI)-based chatbots can offer personalized, engaging, and on-demand health promotion interventions.

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

Journal of biomedical semantics
BACKGROUND: Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically important in an age of greater pollution and chemicals in our environment. Environmental health utilizes many differ...

Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.

Frontiers in public health
OBJECTIVE: Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. Machine learning algorithms were used in this study to predict p...

Spinal disease diagnosis assistant based on MRI images using deep transfer learning methods.

Frontiers in public health
INTRODUCTION: In light of the potential problems of missed diagnosis and misdiagnosis in the diagnosis of spinal diseases caused by experience differences and fatigue, this paper investigates the use of artificial intelligence technology for auxiliar...

Support of deep learning to classify vocal fold images in flexible laryngoscopy.

American journal of otolaryngology
PURPOSE: To collect a dataset with adequate laryngoscopy images and identify the appearance of vocal folds and their lesions in flexible laryngoscopy images by objective deep learning models.

A deep learning system for heart failure mortality prediction.

PloS one
Heart failure (HF) is the final stage of the various heart diseases developing. The mortality rates of prognosis HF patients are highly variable, ranging from 5% to 75%. Evaluating the all-cause mortality of HF patients is an important means to avoid...

A 3-DoF robotic platform for the rehabilitation and assessment of reaction time and balance skills of MS patients.

PloS one
The central nervous system (CNS) exploits anticipatory (APAs) and compensatory (CPAs) postural adjustments to maintain the balance. The postural adjustments comprising stability of the center of mass (CoM) and the pressure distribution of the body in...

Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence-assisted workflow.

Cytometry. Part B, Clinical cytometry
Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important prognostic marker. The most common CLL MRD method in current use is multiparameter flow cytometry, but availability is limited by the need for expert...