AIMC Topic: Algorithms

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Responsible AI in student management: preventing misdecision in career choice of university students under inaccurate guidance.

Scientific reports
In today's digital era, university students' career-related decision-making has become increasingly complex, shaped not only by personal aspirations and societal expectations but also by the algorithmic recommendations embedded in AI-supported techno...

Enhancing gesture recognition for assisting visually impaired persons using deep learning in an IoT environment-based improved snake optimisation algorithm.

Scientific reports
Gesture recognition (GR) is an emerging and wide-ranging area of research. GR is extensively applied in sign language, Immersive game technology, and other computer interfaces, among others. People with visual impairments face challenges in completin...

HSSAM-Net: hyper-scale shifted aggregation network for precise colorectal polyp segmentation in endoscopic images.

Scientific reports
Colorectal cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the importance of early detection through accurate polyp identification. However, colonoscopy relies heavily on precise polyp segmentation in endoscopic imag...

ClairS-TO: a deep-learning method for long-read tumor-only somatic small variant calling.

Nature communications
Accurate detection of somatic variants in tumors is of critical importance and remains challenging. Current methods typically require matched normal samples for reliable detection, which are often unavailable in real-world research and clinical scena...

Comparative study of coronary artery disease prediction: conventional QRISK3 versus enhanced machine learning models combined with particle swarm optimisation algorithm.

Open heart
BACKGROUND: Coronary artery disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known to overestimate future CAD risk in some populations...

Discovering sensorimotor agency in cellular automata using diversity search.

Science advances
The field of artificial life studies how life-like phenomena such as agency and self-regulation can self-organize in computer simulations. In cellular automata (CA), a key open question is whether it is possible to find environment rules that self-or...

A review of the application of deep learning in thyroid nodule imaging: from model architectures to training methods and core image analysis tasks.

Biomedical physics & engineering express
Thyroid nodules are highly prevalent in clinical practice, and their incidence has been steadily increasing in recent years, posing significant threats to human health. Traditional imaging examinations for thyroid nodules rely heavily on physicians' ...

A novel channel reduction concept to enhance the classification of motor imagery tasks in brain-computer interface systems.

PloS one
Electroencephalogram (EEG) signals play a critical role in advancing brain-computer interface (BCI) systems, particularly for detecting motor imagery (MI) movements. However, analysing large volume of EEG datasets faces some challenges due to redunda...

Machine learning algorithms for predicting and identifying the influencing predictors of antenatal care visits among women in Bangladesh: Evidence from BDHS 2022 data.

PloS one
BACKGROUND AND OBJECTIVE: Bangladesh, a South Asian country, continues to face significant challenges in maternal health, as reflected by its high maternal mortality ratio (MMR). According to the 2022 Bangladesh Demographic and Health Survey (BDHS), ...

An interpretable and balanced machine learning framework for Parkinson's disease prediction using feature engineering and explainable AI.

PloS one
Parkinson's disease (PD) is a progressive neurological disorder that affects millions globally, posing significant challenges in early and accurate diagnosis. Recent advancements in machine learning (ML) offer promising approaches for addressing thes...