AIMC Topic: Algorithms

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Do green finance and green innovation affect corporate credit rating performance? Evidence from machine learning approach.

Journal of environmental management
This study investigates the impact of green finance (GF) and green innovation (GI) on corporate credit rating (CR) performance in Chinese A-share listed firms from 2018 to 2021. The least absolute shrinkage and selection operators (LASSOs) machine le...

Electrocardiography Classification with Leaky Integrate-and-Fire Neurons in an Artificial Neural Network-Inspired Spiking Neural Network Framework.

Sensors (Basel, Switzerland)
Monitoring heart conditions through electrocardiography (ECG) has been the cornerstone of identifying cardiac irregularities. Cardiologists often rely on a detailed analysis of ECG recordings to pinpoint deviations that are indicative of heart anomal...

Deep Learning-Based Nystagmus Detection for BPPV Diagnosis.

Sensors (Basel, Switzerland)
In this study, we propose a deep learning-based nystagmus detection algorithm using video oculography (VOG) data to diagnose benign paroxysmal positional vertigo (BPPV). Various deep learning architectures were utilized to develop and evaluate nystag...

NPEX: Never give up protein exploration with deep reinforcement learning.

Journal of molecular graphics & modelling
Elucidating unknown structures of proteins, such as metastable states, is critical in designing therapeutic agents. Protein structure exploration has been performed using advanced computational methods, especially molecular dynamics and Markov chain ...

Machine learning model with output correction: Towards reliable bradycardia detection in neonates.

Computers in biology and medicine
Bradycardia is a commonly occurring condition in premature infants, often causing serious consequences and cardiovascular complications. Reliable and accurate detection of bradycardia events is pivotal for timely intervention and effective treatment....

An effective ensemble learning approach for classification of glioma grades based on novel MRI features.

Scientific reports
The preoperative diagnosis of brain tumors is important for therapeutic planning as it contributes to the tumors' prognosis. In the last few years, the development in the field of artificial intelligence and machine learning has contributed greatly t...

Intelligent wearable olfactory interface for latency-free mixed reality and fast olfactory enhancement.

Nature communications
Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidab...

Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip.

Nature communications
By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms t...

Automated glioblastoma patient classification using hypoxia levels measured through magnetic resonance images.

BMC neuroscience
INTRODUCTION: The challenge of treating Glioblastoma (GBM) tumors is due to various mechanisms that make the tumor resistant to radiation therapy. One of these mechanisms is hypoxia, and therefore, determining the level of hypoxia can improve treatme...

Prediction of 30-Day Mortality Following Revision Total Hip and Knee Arthroplasty: Machine Learning Algorithms Outperform CARDE-B, 5-Item, and 6-Item Modified Frailty Index Risk Scores.

The Journal of arthroplasty
BACKGROUND: Although risk calculators are used to prognosticate postoperative outcomes following revision total hip and knee arthroplasty (total joint arthroplasty [TJA]), machine learning (ML) based predictive tools have emerged as a promising alter...