AIMC Topic: Artificial Intelligence

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DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data.

BMC bioinformatics
BACKGROUND: DNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment ...

Predictive Models for Health Deterioration: Understanding Disease Pathways for Personalized Medicine.

Annual review of biomedical engineering
Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed in medicine and healthcare. A PubMed search returns more than 100,000 articles on these topics published between 2018 and 2022 alone. Notwithstanding several...

Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT.

Diagnostic and interventional imaging
Artificial intelligence has demonstrated utility and is increasingly being used in the field of radiology. The use of generative pre-trained transformer (GPT)-based models has the potential to revolutionize the field of radiology, offering new possib...

Edge computing on TPU for brain implant signal analysis.

Neural networks : the official journal of the International Neural Network Society
The ever-increasing number of recording sites of silicon-based probes imposes a great challenge for detecting and evaluating single-unit activities in an accurate and efficient manner. Currently separate solutions are available for high precision off...

A review of biowaste remediation and valorization for environmental sustainability: Artificial intelligence approach.

Environmental pollution (Barking, Essex : 1987)
Biowaste remediation and valorization for environmental sustainability focuses on prevention rather than cleanup of waste generation by applying the fundamental recovery concept through biowaste-to-bioenergy conversion systems - an appropriate approa...

Application of Artificial Intelligence to Quantitative Assessment of Fundus Tessellated Density in Young Adults with Different Refractions.

Ophthalmic research
INTRODUCTION: The aim of this study was to quantitatively assess fundus tessellated density (FTD) and associated factors by artificial intelligence (AI) in young adults.

Deep Learning-Based Acceleration of Compressed Sensing for Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The clinical application of coronary MR angiography (MRA) remains limited due to its long acquisition time and often unsatisfactory image quality. A compressed sensing artificial intelligence (CSAI) framework was recently introduced to ov...

Automatic placental and fetal volume estimation by a convolutional neural network.

Placenta
INTRODUCTION: We aimed to develop an artificial intelligence (AI) deep learning algorithm to efficiently estimate placental and fetal volumes from magnetic resonance (MR) scans.