AIMC Topic: Artificial Intelligence

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Beyond spiking networks: The computational advantages of dendritic amplification and input segregation.

Proceedings of the National Academy of Sciences of the United States of America
The brain can efficiently learn a wide range of tasks, motivating the search for biologically inspired learning rules for improving current artificial intelligence technology. Most biological models are composed of point neurons and cannot achieve st...

Identifying Explainable Machine Learning Models and a Novel SFRP2 Fibroblast Signature as Predictors for Precision Medicine in Ovarian Cancer.

International journal of molecular sciences
Ovarian cancer (OC) is a type of malignant tumor with a consistently high mortality rate. The diagnosis of early-stage OC and identification of functional subsets in the tumor microenvironment are essential to the development of patient management st...

Enzyme Databases in the Era of Omics and Artificial Intelligence.

International journal of molecular sciences
Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over...

Deep Learning Approaches for Automatic Quality Assurance of Magnetic Resonance Images Using ACR Phantom.

BMC medical imaging
BACKGROUND: In recent years, there has been a growing trend towards utilizing Artificial Intelligence (AI) and machine learning techniques in medical imaging, including for the purpose of automating quality assurance. In this research, we aimed to de...

Artificial intelligence-based forensic sex determination of East Asian cadavers from skull morphology.

Scientific reports
Identification of unknown cadavers is an important task for forensic scientists. Forensic scientists attempt to identify skeletal remains based on factors including age, sex, and dental treatment remains. Forensic scientists commonly consider skull o...

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach.

Scientific reports
Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers ...

Enhancing diagnosis of Hirschsprung's disease using deep learning from histological sections of post pull-through specimens: preliminary results.

Pediatric surgery international
PURPOSE: Accurate histological diagnosis in Hirschsprung disease (HD) is challenging, due to its complexity and potential for errors. In this study, we present an artificial intelligence (AI)-based method designed to identify ganglionic cells and hyp...

Empowering Medical Students: Harnessing Artificial Intelligence for Precision Point-of-Care Echocardiography Assessment of Left Ventricular Ejection Fraction.

International journal of clinical practice
INTRODUCTION: Point-of-care ultrasound (POCUS) use is now universal among nonexperts. Artificial intelligence (AI) is currently employed by nonexperts in various imaging modalities to assist in diagnosis and decision making.

A robust optimal control by grey wolf optimizer for underwater vehicle-manipulator system.

PloS one
Underwater vehicle-manipulator system (UVMS) is a commonly used underwater operating equipment. Its control scheme has been the focus of control researchers, as it operates in the presence of lumped disturbances, including modelling uncertainties and...