AIMC Topic: Machine Learning

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Learning the impact of acute and chronic diseases on forecasting neonatal encephalopathy.

Computer methods and programs in biomedicine
OBJECTIVE: There is a wide range of risk factors predisposing to the onset of neonatal encephalopathy (NE), including maternal antepartum/intrapartum comorbidities or events. However, few studies have investigated the difference in the impact of acut...

[Digitalized psychiatry : Critical considerations on a new paradigm].

Der Nervenarzt
Digitalization and artificial intelligence hold the prospect of new procedures for psychiatry. Machine learning techniques combined with big data should enable algorithmized diagnostics, prediction and therapy that are superior to clinical observatio...

ConAnomaly: Content-Based Anomaly Detection for System Logs.

Sensors (Basel, Switzerland)
Enterprise systems typically produce a large number of logs to record runtime states and important events. Log anomaly detection is efficient for business management and system maintenance. Most existing log-based anomaly detection methods use log pa...

Non-invasive health prediction from visually observable features.

F1000Research
The unprecedented development of Artificial Intelligence has revolutionised the healthcare industry. In the next generation of healthcare systems, self-diagnosis will be pivotal to personalised healthcare services. During the COVID-19 pandemic, new ...

A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection.

Computational and mathematical methods in medicine
Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous...

A Few-Shot Learning-Based Siamese Capsule Network for Intrusion Detection with Imbalanced Training Data.

Computational intelligence and neuroscience
Network intrusion detection remains one of the major challenges in cybersecurity. In recent years, many machine-learning-based methods have been designed to capture the dynamic and complex intrusion patterns to improve the performance of intrusion de...

State Evaluation Method of Robot Lubricating Oil Based on Support Vector Regression.

Computational intelligence and neuroscience
Recently, the development of the Industrial Internet of Things (IIoT) has led enterprises to re-examine the research of the equipment-state-prediction models and intelligent manufacturing applications. Take industrial robots as typical example. Under...

Marketable value estimation of patents using ensemble learning methodology: Focusing on U.S. patents for the electricity sector.

PloS one
Patent valuation is required to revitalize patent transactions, but calculating a reasonable value that consumers and suppliers could satisfy is difficult. When machine learning is used, a quantitative evaluation based on a large volume of data is po...

Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers.

BMC medical informatics and decision making
BACKGROUND: It is essential for radiologists to communicate actionable findings to the referring clinicians reliably. Natural language processing (NLP) has been shown to help identify free-text radiology reports including actionable findings. However...

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

BioMed research international
The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel f...