AIMC Topic: Humans

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Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

Respiration; international review of thoracic diseases
INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impact on hospitalizations, morbidity, and mortality of patients. This study aimed to develop a model for predicting acute exacerbation in COPD patients (A...

New developments in the application of artificial intelligence to laryngology.

Current opinion in otolaryngology & head and neck surgery
PURPOSE OF REVIEW: The purpose of this review is to summarize the existing literature on artificial intelligence technology utilization in laryngology, highlighting recent advances and current barriers to implementation.

CT-based artificial intelligence prediction model for ocular motility score of thyroid eye disease.

Endocrine
PURPOSE: Thyroid eye disease (TED) is the most common orbital disease in adults. Ocular motility restriction is the primary complaint of patients, while its evaluation is quite difficult. The present study aimed to introduce an artificial intelligenc...

PSAR-SR: Patches separation and artifacts removal for improving super-resolution networks.

Neural networks : the official journal of the International Neural Network Society
The success of the ClassSR has led to a strategy of decomposing images being used for large image SR. The decomposed image patches have different recovery difficulties. Therefore, in ClassSR, image patches are reconstructed by different networks to g...

Adaptive self-supervised learning for sequential recommendation.

Neural networks : the official journal of the International Neural Network Society
Sequential recommendation typically utilizes deep neural networks to mine rich information in interaction sequences. However, existing methods often face the issue of insufficient interaction data. To alleviate the sparsity issue, self-supervised lea...

Differentiable self-supervised clustering with intrinsic interpretability.

Neural networks : the official journal of the International Neural Network Society
Self-supervised clustering has garnered widespread attention due to its ability to discover latent clustering structures without the need for external labels. However, most existing approaches on self-supervised clustering lack of inherent interpreta...

3D printed dosage forms, where are we headed?

Expert opinion on drug delivery
INTRODUCTION: 3D Printing (3DP) is an innovative fabrication technology that has gained enormous popularity through its paradigm shifts in manufacturing in several disciplines, including healthcare. In this past decade, we have witnessed the impact o...

Artificial intelligence and machine learning for anaphylaxis algorithms.

Current opinion in allergy and clinical immunology
PURPOSE OF REVIEW: Anaphylaxis is a severe, potentially life-threatening allergic reaction that requires rapid identification and intervention. Current management includes early recognition, prompt administration of epinephrine, and immediate medical...

Physical therapists' perceptions and attitudes towards artificial intelligence in healthcare and rehabilitation: A qualitative study.

Musculoskeletal science & practice
BACKGROUND: Artificial intelligence (AI) is being introduced to rehabilitation practices, and it can optimize the patient's outcome through their ability to design personalized care strategies and interventions.

Machine learning computational model to predict lung cancer using electronic medical records.

Cancer epidemiology
BACKGROUND: Lung cancer (LC) screening using low-dose computed tomography (CT) is recommended according to standard risk criteria or personalized risk calculators. Machine learning (ML) models that can predict disease risk are an emerging method in m...