AIMC Topic: Artificial Intelligence

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Neural Network in the Analysis of the MR Signal as an Image Segmentation Tool for the Determination of T and T Relaxation Times with Application to Cancer Cell Culture.

International journal of molecular sciences
Artificial intelligence has been entering medical research. Today, manufacturers of diagnostic instruments are including algorithms based on neural networks. Neural networks are quickly entering all branches of medical research and beyond. Analyzing ...

Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.

International journal of environmental research and public health
(1) Introduction: Around a million people are reported to die by suicide every year, and due to the stigma associated with the nature of the death, this figure is usually assumed to be an underestimate. Machine learning and artificial intelligence su...

Ethics and governance of trustworthy medical artificial intelligence.

BMC medical informatics and decision making
BACKGROUND: The growing application of artificial intelligence (AI) in healthcare has brought technological breakthroughs to traditional diagnosis and treatment, but it is accompanied by many risks and challenges. These adverse effects are also seen ...

Variational autoencoder-based estimation of chronological age and changes in morphological features of teeth.

Scientific reports
This study led to the development of a variational autoencoder (VAE) for estimating the chronological age of subjects using feature values extracted from their teeth. Further, it determined how given teeth images affected the estimation accuracy. The...

An Accurate Deep Learning-Based System for Automatic Pill Identification: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Medication errors account for a large proportion of all medical errors. In most homes, patients take a variety of medications for a long period. However, medication errors frequently occur because patients often throw away the containers ...

Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.

Journal of medical systems
Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in...

Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation.

Journal of medical Internet research
BACKGROUND: Osteoporosis is one of the diseases that requires early screening and detection for its management. Common clinical tools and machine-learning (ML) models for screening osteoporosis have been developed, but they show limitations such as l...

Applications of Artificial Intelligence and Deep Learning in Glaucoma.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Diagnosis and detection of progression of glaucoma remains challenging. Artificial intelligence-based tools have the potential to improve and standardize the assessment of glaucoma but development of these algorithms is difficult given the multimodal...

Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models.

European journal of nuclear medicine and molecular imaging
PURPOSE: To provide a holistic and complete comparison of the five most advanced AI models in the augmentation of low-dose F-FDG PET data over the entire dose reduction spectrum.