AIMC Topic: Humans

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A multi-class fundus disease classification system based on an adaptive scale discriminator and hybrid loss.

Computational biology and chemistry
Fundus images are crucial in the observation and detection of ophthalmic diseases. However, detecting multiple ophthalmic diseases from fundus images using deep learning techniques is a complex and challenging task One challenge is the complexity of ...

Diagnostic accuracy of artificial intelligence for approximal caries on bitewing radiographs: A systematic review and meta-analysis.

Journal of dentistry
OBJECTIVES: This systematic review and meta-analysis aimed to investigate the diagnostic accuracy of Artificial Intelligence (AI) for approximal carious lesions on bitewing radiographs.

AI driven interpretable deep learning based fetal health classification.

SLAS technology
In this study, a deep learning model is proposed for the classification of fetal health into 3 categories: Normal, suspect, and pathological. The primary objective is to utilize the power of deep learning to improve the efficiency and effectiveness o...

Automation of biochemical assays using an open-sourced, inexpensive robotic liquid handler.

SLAS technology
High Throughput Screening is crucial in pharmaceutical companies for efficient testing in drug discovery and development. Our Vaccines Analytical Research and Development (V-AR&D) department extensively uses robotic liquid handlers in their High Thro...

Machine Learning for Prediction of Postoperative Delirium in Adult Patients: A Systematic Review and Meta-analysis.

Clinical therapeutics
PURPOSE: This meta-analysis aimed to evaluate the performance of machine learning (ML) models in predicting postoperative delirium (POD) and to provide guidance for clinical application.

Current status and dilemmas of osteoporosis screening tools: A narrative review.

Clinical nutrition ESPEN
OBJECTIVE: This review aims to explore the strengths and dilemmas of existing osteoporosis screening tools and suggest possible ways of optimization, in addition to exploring the potential of AI-integrated X-ray imaging in osteoporosis screening, esp...

gGN: Representing the Gene Ontology as low-rank Gaussian distributions.

Computers in biology and medicine
Computational representations of knowledge graphs are critical for several tasks in bioinformatics, including large-scale graph analysis and gene function characterization. In this study, we introduce gGN, an unsupervised neural network for learning ...

Segmentation of four-chamber view images in fetal ultrasound exams using a novel deep learning model ensemble method.

Computers in biology and medicine
Fetal echocardiography, a specialized ultrasound application commonly utilized for fetal heart assessment, can greatly benefit from automated segmentation of anatomical structures, aiding operators in their evaluations. We introduce a novel approach ...

Quantifying the use and potential benefits of artificial intelligence in scientific research.

Nature human behaviour
The rapid advancement of artificial intelligence (AI) is poised to reshape almost every line of work. Despite enormous efforts devoted to understanding AI's economic impacts, we lack a systematic understanding of the benefits to scientific research a...