AIMC Topic: Artificial Intelligence

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Automatic Segmentation and Classification for Antinuclear Antibody Images Based on Deep Learning.

Computational intelligence and neuroscience
Antinuclear antibodies (ANAs) testing is the main serological diagnosis screening test for autoimmune diseases. ANAs testing is conducted principally by the indirect immunofluorescence (IIF) on human epithelial cell-substrate (HEp-2) protocol. Howeve...

Multimodal convolutional neural networks based on the Raman spectra of serum and clinical features for the early diagnosis of prostate cancer.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
We collected surface-enhanced Raman spectroscopy (SERS) data from the serum of 729 patients with prostate cancer or benign prostatic hyperplasia (BPH), corresponding to their pathological results, and built an artificial intelligence-assisted diagnos...

Video-Based Deep Learning for Automated Assessment of Left Ventricular Ejection Fraction in Pediatric Patients.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Significant interobserver and interstudy variability occurs for left ventricular (LV) functional indices despite standardization of measurement techniques. Artificial intelligence models trained on adult echocardiograms are not likely to ...

Assessment of artificial intelligence (AI) reporting methodology in glioma MRI studies using the Checklist for AI in Medical Imaging (CLAIM).

Neuroradiology
PURPOSE: The Checklist for Artificial Intelligence in Medical Imaging (CLAIM) is a recently released guideline designed for the optimal reporting methodology of artificial intelligence (AI) studies. Gliomas are the most common form of primary maligna...

The Evidence for Using Artificial Intelligence to Enhance Prostate Cancer MR Imaging.

Current oncology reports
PURPOSE OF REVIEW: The purpose of this review is to summarize the current status of artificial intelligence applied to prostate cancer MR imaging.

Resolving the associative learning paradox by category learning in pigeons.

Current biology : CB
A wealth of evidence indicates that humans can engage two types of mechanisms to solve category-learning tasks: declarative mechanisms, which involve forming and testing verbalizable decision rules, and associative mechanisms, which involve gradually...

A Blanket That Leaves the Feet Cold: Exploring the AI Act Safety Framework for Medical AI.

European journal of health law
The AI Act is based on, and at the same time aims to protect fundamental rights, implying their protection, while fulfilling the safety requirement prescribed by the AI Act within the whole lifecycle of AI systems. Based on a risk classification, the...

Shape classification technology of pollinated tomato flowers for robotic implementation.

Scientific reports
Three pollination methods are commonly used in the greenhouse cultivation of tomato. These are pollination using insects, artificial pollination (by manually vibrating flowers), and plant growth regulators. Insect pollination is the preferred natural...

The role of artificial intelligence in the treatment of obstructive sleep apnea.

Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
BACKGROUND: The first-line and most common treatment for obstructive sleep apnea is nasal continuous positive airway pressure, which serves as a pneumatic splint to stabilize the upper airway and is effective when used with appropriate adherence. Con...

Automating the Standardized Cosmesis and Health Nasal Outcomes Survey Classification with Convolutional Neural Networks.

Facial plastic surgery & aesthetic medicine
Currently, the aesthetic appearance and structure of the nose in a rhinoplasty patient is evaluated by a surgeon, without automation. To compare the assessment of convolutional neural networks (CNNs) (machine learning) and a rhinoplasty surgeon's i...