AIMC Topic: Machine Learning

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Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning.

PloS one
In the production sector, the usefulness of predictive systems as a tool for management and decision-making is well known. In the agricultural sector, a correct economic balance of the farm depends on making the right decisions. For this purpose, hav...

Robust Path Planning via Learning From Demonstrations for Robotic Catheters in Deformable Environments.

IEEE transactions on bio-medical engineering
OBJECTIVE: Navigation through tortuous and deformable vessels using catheters with limited steering capability underscores the need for reliable path planning. State-of-the-art path planners do not fully account for the deformable nature of the envir...

Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study.

Frontiers in public health
OBJECTIVE: Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.

A cross-sectional study of parental perspectives on children about COVID-19 and classification using machine learning models.

Frontiers in public health
BACKGROUND AND OBJECTIVE: This study delves into the parenting cognition perspectives on COVID-19 in children, exploring symptoms, transmission modes, and protective measures. It aims to correlate these perspectives with sociodemographic factors and ...

Human or Machine? A Comparative Analysis of Artificial Intelligence-Generated Writing Detection in Personal Statements.

Journal, physical therapy education
INTRODUCTION: This study examines the ability of human readers, recurrence quantification analysis (RQA), and an online artificial intelligence (AI) detection tool (GPTZero) to distinguish between AI-generated and human-written personal statements in...

Artificial intelligence in healthcare applications targeting cancer diagnosis-part I: data structure, preprocessing and data organization.

Oral surgery, oral medicine, oral pathology and oral radiology
BACKGROUND: Machine learning techniques hold significant potential to support the diagnosis and prognosis of diseases. However, the success of these approaches is heavily dependent on rigorous data acquisition, preprocessing and data organization.

A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index.

Neural networks : the official journal of the International Neural Network Society
For imbalanced classification problem, algorithm-level methods can effectively avoid the information loss and noise introduction of data-level methods. However, the differences in the characteristics of the datasets, such as imbalance ratio, data dim...

Fuzzy bifocal disambiguation for partial multi-label learning.

Neural networks : the official journal of the International Neural Network Society
In partial multi-label learning (PML), each instance is associated with multiple candidate labels, but only a subset is the ground-truth label. Due to the ambiguous label information, PML is more challenging than traditional multi-label learning. Con...

Interpretable machine learning models for COPD ease of breathing estimation.

Medical & biological engineering & computing
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide and greatly reduces the quality of life. Utilizing remote monitoring has been shown to improve quality of life and reduce exacerbations, but remains an ongoing area of...

Dynamic spectrum-driven hierarchical learning network for polyp segmentation.

Medical image analysis
Accurate automatic polyp segmentation in colonoscopy is crucial for the prompt prevention of colorectal cancer. However, the heterogeneous nature of polyps and differences in lighting and visibility conditions present significant challenges in achiev...