Particle swarm optimization in biomedical technologies: innovations, challenges, and opportunities

K Suriyan, R Nagarajan - … for Health Literacy and Medical Practice, 2024 - igi-global.com
This chapter explores particle swarm optimization (PSO) in the rapidly evolving landscape of
biomedical technologies. The study begins by introducing the fundamental principles of …

Reviewing the role of AI in environmental monitoring and conservation: A data-driven revolution for our planet

ON Chisom, PW Biu, AA Umoh, BO Obaedo… - World Journal of …, 2024 - wjarr.com
The rapid increase in human activities is causing significant damage to our planet's
ecosystems, necessitating innovative solutions to preserve biodiversity and counteract …

[HTML][HTML] Interpretable radiomic signature for breast microcalcification detection and classification

F Prinzi, A Orlando, S Gaglio, S Vitabile - Journal of Imaging Informatics in …, 2024 - Springer
Breast microcalcifications are observed in 80% of mammograms, and a notable proportion
can lead to invasive tumors. However, diagnosing microcalcifications is a highly complicated …

[HTML][HTML] Introducing an Artificial Neural Network for Virtually Increasing the Sample Size of Bioequivalence Studies

D Papadopoulos, VD Karalis - Applied Sciences, 2024 - mdpi.com
Sample size is a key factor in bioequivalence and clinical trials. An appropriately large
sample is necessary to gain valuable insights into a designated population. However, large …

Improving Generation and Evaluation of Long Image Sequences for Embryo Development Prediction

P Celard, A Seara Vieira, JM Sorribes-Fdez… - Electronics, 2024 - mdpi.com
Generating synthetic time series data, such as videos, presents a formidable challenge as
complexity increases when it is necessary to maintain a specific distribution of shown …

Breast Cancer Diagnosis Method Based on Cross-Mammogram Four-View Interactive Learning

X Wen, J Li, L Yang - Tomography, 2024 - mdpi.com
Computer-aided diagnosis systems play a crucial role in the diagnosis and early detection of
breast cancer. However, most current methods focus primarily on the dual-view analysis of a …

Advancements in Medical Imaging: A Transition From Machine Learning to Deep Learning

V Grover, P Pal, M Nandal - … Explainable AI in Healthcare and the …, 2024 - igi-global.com
Medical imaging holds a pivotal role in modern healthcare, facilitating early disease
identification, treatment planning, and patient progress monitoring. The integration of …

A Short Survey on Multimodal Data Fusion in Image Classification

T Datsi, K Aznag, BA BenAli, K Karbout… - 2024 International …, 2024 - ieeexplore.ieee.org
Advancements in multimodal learning have experienced rapid growth over the past decade,
particularly within various domains, with a significant emphasis on developments in …

[PDF][PDF] Advancements in Neurosurgery: Minimally Invasive Robotics and AI-Driven Generative Architectures

T Graepel - 2023 - researchgate.net
Recent advancements in neurosurgery have been significantly influenced by the integration
of minimally invasive robotic technologies and AI-driven generative architectures. Minimally …

[PDF][PDF] Neurosurgery Advancements: Minimally Invasive Robotics and Generative AI Architectures

O Troisi, F Akram - researchgate.net
Recent advancements in neurosurgery have witnessed significant progress in two key
areas: minimally invasive robotics and generative AI architectures. Minimally invasive …