AIMC Topic: Machine Learning

Clear Filters Showing 29491 to 29500 of 34417 articles

TransembleNet: Enhancing vector mosquito species classification through transfer learning-based ensemble model.

PloS one
Mosquitoes, which belong to diverse species, play a significant role in ecological systems and public health. The accurate identification (classification) of mosquito species is essential for a comprehensive understanding of their ecological roles, b...

Behavior classification: Introducing machine learning approaches for classification of sign-tracking, goal-tracking and beyond.

PloS one
Classifying behaviors in research often relies on predetermined or subjective cutoff values, which can introduce inconsistencies and reduce objectivity. For example, in Pavlovian conditioning studies, rodents display diverse behaviors which can be qu...

Tumor-infiltrating immune cell signature score reveals prognostic biomarkers and therapeutic targets for colorectal cancer.

Frontiers in immunology
BACKGROUND: Colorectal cancer (CRC) is one of the leading contributors to cancer-related deaths worldwide, with more than 900,000 new diagnoses and related deaths each year. This study aims to explore the prognostic value of tumor-infiltrating immune...

TWINVAX: conceptual model of a digital twin for immunisation services in primary health care.

Frontiers in public health
INTRODUCTION: This paper presents a proposal for the modelling and reference architecture of a digital twin for immunisation services in primary health care centres. The system leverages Industry 4.0 concepts and technologies, such as the Internet of...

IoT and ML-driven framework for managing infectious disease risks in communal spaces: a post-COVID perspective.

Frontiers in public health
COVID-19 has not only changed the way people live but has also altered the way all organizations operate. The most effective precautionary measure against the spread of the virus that caused the COVID-19 pandemic SARS-CoV-2, is to use face coverings ...

Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.

PloS one
CONTEXT AND BACKGROUND: Depression has affected millions of people worldwide and has become one of the most common mental disorders. Early mental disorder detection can reduce costs for public health agencies and prevent other major comorbidities. Ad...

Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM.

PloS one
Artificial Intelligence (AI) is being integrated into increasingly more domains of everyday activities. Whereas AI has countless benefits, its convoluted and sometimes vague internal operations can establish difficulties. Nowadays, AI is significantl...

A scoping review and quality assessment of machine learning techniques in identifying maternal risk factors during the peripartum phase for adverse child development.

PloS one
Maternal exposure to environmental risk factors (e.g., heavy metal exposure) or mental health problems during the peripartum phase has been shown to lead to negative and lasting impacts on child development and life in adulthood. Given the importance...

Odor classification: Exploring feature performance and imbalanced data learning techniques.

PloS one
This research delves into olfaction, a sensory modality that remains complex and inadequately understood. We aim to fill in two gaps in recent studies that attempted to use machine learning and deep learning approaches to predict human smell percepti...