AIMC Topic: Machine Learning

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A survey of machine learning-based methods for COVID-19 medical image analysis.

Medical & biological engineering & computing
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December 2019. Hence, rapid and accu...

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases.

Sensors (Basel, Switzerland)
Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. These have emerged as one of the most concerning health conditions over the last two decades, after cancer around the world. The early diagnosis of COP...

Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China.

Frontiers in public health
BACKGROUND: Considering that the previously developed mortality prediction models have limited applications to the Chinese population, a questionnaire-based prediction model is of great importance for its accuracy and convenience in clinical practice...

Domain generation algorithms detection with feature extraction and Domain Center construction.

PloS one
Network attacks using Command and Control (C&C) servers have increased significantly. To hide their C&C servers, attackers often use Domain Generation Algorithms (DGA), which automatically generate domain names for C&C servers. Researchers have const...

Artificial intelligence and machine learning as a viable solution for hip implant failure diagnosis-Review of literature and in vitro case study.

Medical & biological engineering & computing
The digital health industry is experiencing fast-paced research which can provide digital care programs and technologies to enhance the competence of healthcare delivery. Orthopedic literature also confirms the applicability of artificial intelligenc...

A hybrid intelligent model for early validation of infectious diseases: An explorative study of machine learning approaches.

Microscopy research and technique
Literature reports several infectious diseases news validation approaches, but none is economically effective for collecting and classifying information on different infectious diseases. This work presents a hybrid machine-learning model that could p...

Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population.

NeuroImage
In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or do not have acceptable quality due to issues with subject compliance, equipment failure or signal error. In large databases, such as the Human Connec...

Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diag...

Avoiding bias in artificial intelligence.

International forum of allergy & rhinology
Artificial intelligence (AI) is ubiquitous and expanding, and the healthcare industry has rapidly adopted AI and machine learning for numerous applications. It is essential to understand that AI is not immune to the biases that impact our clinical an...