AIMC Topic: Algorithms

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Cardiac patients' surgery outcome and associated factors in Ethiopia: application of machine learning.

BMC pediatrics
INTRODUCTION: Cardiovascular diseases are a class of heart and blood vessel-related illnesses. In Sub-Saharan Africa, including Ethiopia, preventable heart disease continues to be a significant factor, contrasting with its presence in developed natio...

Predicting severity of acute appendicitis with machine learning methods: a simple and promising approach for clinicians.

BMC emergency medicine
BACKGROUNDS: Acute Appendicitis (AA) is one of the most common surgical emergencies worldwide. This study aims to investigate the predictive performances of 6 different Machine Learning (ML) algorithms for simple and complicated AA.

An extensive analysis of artificial intelligence and segmentation methods transforming cancer recognition in medical imaging.

Biomedical physics & engineering express
Recent advancements in computational intelligence, deep learning, and computer-aided detection have had a significant impact on the field of medical imaging. The task of image segmentation, which involves accurately interpreting and identifying the c...

CAManim: Animating end-to-end network activation maps.

PloS one
Deep neural networks have been widely adopted in numerous domains due to their high performance and accessibility to developers and application-specific end-users. Fundamental to image-based applications is the development of Convolutional Neural Net...

A high-accuracy lightweight network model for X-ray image diagnosis: A case study of COVID detection.

PloS one
The Coronavirus Disease 2019(COVID-19) has caused widespread and significant harm globally. In order to address the urgent demand for a rapid and reliable diagnostic approach to mitigate transmission, the application of deep learning stands as a viab...

An optimized deep strategy for recognition and alleviation of DDoS attack in SD-IoT.

Network (Bristol, England)
The attacks like distributed denial-of-service (DDoS) are termed as severe defence issues in data centres, and are considered real network threat. These types of attacks can produce huge disturbances in information technologies. In addition, it is a ...

Expert-level detection of M-proteins in serum protein electrophoresis using machine learning.

Clinical chemistry and laboratory medicine
OBJECTIVES: Serum protein electrophoresis (SPE) in combination with immunotyping (IMT) is the diagnostic standard for detecting monoclonal proteins (M-proteins). However, interpretation of SPE and IMT is weakly standardized, time consuming and invest...

Classification of Parkinson's disease severity using gait stance signals in a spatiotemporal deep learning classifier.

Medical & biological engineering & computing
Parkinson's disease (PD) is a degenerative nervous system disorder involving motor disturbances. Motor alterations affect the gait according to the progression of PD and can be used by experts in movement disorders to rate the severity of the disease...

Leveraging temporal dependency for cross-subject-MI BCIs by contrastive learning and self-attention.

Neural networks : the official journal of the International Neural Network Society
Brain-computer interfaces (BCIs) built based on motor imagery paradigm have found extensive utilization in motor rehabilitation and the control of assistive applications. However, traditional MI-BCI systems often exhibit suboptimal classification per...

Recent advances in flexible hydrogel sensors: Enhancing data processing and machine learning for intelligent perception.

Biosensors & bioelectronics
With the advent of flexible electronics and sensing technology, hydrogel-based flexible sensors have exhibited considerable potential across a diverse range of applications, including wearable electronics and soft robotics. Recently, advanced machine...